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Designing Effective Data Visualizations

Join Johns Hopkins Data Services in this workshop session to learn design principles and recommended practices for creating effective scientific data visualization.

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• Open access
• Published: 31 August 2024

Effects of pecha kucha presentation pedagogy on nursing students’ presentation skills: a quasi-experimental study in Tanzania

• Setberth Jonas Haramba 1 ,
• Walter C. Millanzi 1 &
• Saada A. Seif 2  

BMC Medical Education volume  24 , Article number:  952 ( 2024 ) Cite this article

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Introduction

Ineffective and non-interactive learning among nursing students limits opportunities for students’ classroom presentation skills, creativity, and innovation upon completion of their classroom learning activities. Pecha Kucha presentation is the new promising pedagogy that engages students in learning and improves students’ speaking skills and other survival skills. It involves the use of 20 slides, each covering 20 seconds of its presentation. The current study examined the effect of Pecha Kucha’s presentation pedagogy on presentation skills among nursing students in Tanzania.

The aim of this study was to establish comparative nursing student’s presentation skills between exposure to the traditional PowerPoint presentations and Pecha Kucha presentations.

The study employed an uncontrolled quasi-experimental design (pre-post) using a quantitative research approach among 230 randomly selected nursing students at the respective training institution. An interviewer-administered structured questionnaire adopted from previous studies to measure presentation skills between June and July 2023 was used. The study involved the training of research assistants, pre-assessment of presentation skills, training of participants, assigning topics to participants, classroom presentations, and post-intervention assessment. A linear regression analysis model was used to determine the effect of the intervention on nursing students’ presentation skills using Statistical Package for Social Solution (SPSS) version 26, set at a 95% confidence interval and 5% significance level.

Findings revealed that 63 (70.87%) participants were aged ≤ 23 years, of which 151 (65.65%) and 189 (82.17%) of them were males and undergraduate students, respectively. Post-test findings showed a significant mean score change in participants’ presentation skills between baseline (M = 4.07 ± SD = 0.56) and end-line (M = 4.54 ± SD = 0.59) that accounted for 0.4717 ± 0.7793; p  < .0001(95%CI) presentation skills mean score change with a medium effect size of 0.78. An increase in participants’ knowledge of Pecha Kucha presentation was associated with a 0.0239 ( p  < .0001) increase in presentation skills.

Pecha Kucha presentations have a significant effect on nursing students’ presentation skills as they enhance inquiry and mastery of their learning content before classroom presentations. The pedagogical approach appeared to enhance nursing students’ confidence during the classroom presentation. Therefore, there is a need to incorporate Pecha Kucha presentation pedagogy into nursing curricula and nursing education at large to promote student-centered teaching and learning activities and the development of survival skills.

Trial registration

It was not applicable as it was a quasi-experimental study.

Peer Review reports

The nursing students need to have different skills acquired during the learning process in order to enable them to provide quality nursing care and management in the society [ 1 ]. The referred nursing care and management practices include identifying, analyzing, synthesizing, and effective communication within and between healthcare professionals [ 1 ]. Given an increasing global economy and international competition for jobs and opportunities, the current traditional classroom learning methods are insufficient to meet such 21st - century challenges and demands [ 2 ]. The integration of presentation skills, creativity, innovation, collaboration, information, and media literacy skills helps to overcome the noted challenges among students [ 2 , 3 , 4 ]. The skills in question constitute the survival skills that help the students not only for career development and success but also for their personal, social and public quality of life as they enable students to overcome 21st challenges upon graduation [ 2 ].

To enhance the nursing students’ participation in learning, stimulating their presentation skills, critical thinking, creativity, and innovation, a combination of teaching and learning pedagogy should be employed [ 5 , 6 , 7 , 8 ]. Among others, classroom presentations, group discussions, problem-based learning, demonstrations, reflection, and role-play are commonly used for those purposes [ 5 ]. However, ineffective and non-interactive learning which contribute to limited presentation skills, creativity, and innovation, have been reported by several scholars [ 9 , 10 , 11 ]. For example, poor use and design of student PowerPoint presentations led to confusing graphics due to the many texts in the slides and the reading of about 80 slides [ 12 , 13 , 14 ]. Indeed, such non-interactive learning becomes boring and tiresome among the learners, and it is usually evidenced by glazing eyes, long yawning, occasional snoring, the use of a phone and frequent trips to the bathroom [ 12 , 14 ].

With an increasing number of nursing students in higher education institutions in Tanzania, the students’ traditional presentation pedagogy is insufficient to stimulate their presentation skills. They limit nursing student innovation, creativity, critical thinking, and meaningful learning in an attempt to solve health challenges [ 15 , 16 ].These hinder nursing students ability to communicate effectively by being able to demonstrate their knowledge and mastery of learning content [ 17 , 18 ]. Furthermore, it affects their future careers by not being able to demonstrate and express their expertise clearly in a variety of workplace settings, such as being able to present at scientific conferences, participating in job interviews, giving clinic case reports, handover reports, and giving feedback to clients [ 17 , 18 , 19 ].

Pecha Kucha presentation is a new promising approach for students’ learning in the classroom context as it motivates learners’ self-directed and collaborative learning, learner creativity, and presentation skills [ 20 , 21 , 22 ]. It encourages students to read more materials, enhances cooperative learning among learners, and is interesting and enjoyable among students [ 23 ].

Pecha Kucha presentation originated from the Japanese word “ chit chat , ” which represents the fast-paced presentation used in different fields, including teaching, marketing, advertising, and designing [ 24 , 25 , 26 ]. It involves 20 slides, where each slide covers 20 s, thus making a total of 6 min and 40 s for the whole presentation [ 22 ]. For effective learning through Pecha Kucha presentations, the design and format of the presentation should be meaningfully limited to 20 slides and targeted at 20 s for each slide, rich in content of the presented topic using high-quality images or pictures attuned to the content knowledge and message to be delivered to the target audiences [ 14 , 16 ]. Each slide should contain a primordial message with well-balanced information. In other words, the message should be simple in the sense that each slide should contain only one concept or idea with neither too much nor too little information, thus making it easy to be grasped by the audience [ 14 , 17 , 19 ].

The “true spirit” of Pecha Kucha is that it mostly consists of powerful images and meaningful specific text rather than the text that is being read by the presenter from the slides, an image, and short phrases that should communicate the core idea while the speaker offers well-rehearsed and elaborated comments [ 22 , 28 ]. The presenter should master the subject matter and incorporate the necessary information from classwork [ 14 , 20 ]. The audience’s engagement in learning by paying attention and actively listening to the Pecha Kucha presentation was higher compared with that in traditional PowerPoint presentations [ 29 ]. The creativity and collaboration during designing and selecting the appropriate images and contents, rehearsal before the presentation, and discussion after each presentation made students satisfied by enjoying Pecha Kucha presentations compared with traditional presentations [ 21 , 22 ]. Time management and students’ self-regulation were found to be significant through the Pecha Kucha presentation among the students and teachers or instructors who could appropriately plan the time for classroom instruction [ 22 , 23 ].

However, little is known about Pecha Kucha presentation in nursing education in Sub-Saharan African countries, including Tanzania, since there is insufficient evidence for the research(s) that have been published on the description of its effects on enhancing students’ presentation skills. Thus, this study assessed the effect of Pecha Kucha’s presentation pedagogy on enhancing presentation skills among nursing students. In particular, the study largely focused on nursing students’ presentation skills during the preparation and presentation of the students’ assignments, project works, case reports, or field reports.

The study answered the null hypothesis H 0  = H 1, which hypothesized that there is no significant difference in nursing students’ classroom presentation skills scores between the baseline and end-line assessments. The association between nursing students’ presentation skills and participants’ sociodemographic characteristics was formulated and analyzed before and after the intervention. This study forms the basis for developing new presentation pedagogy among nursing students in order to stimulate effective learning and the development of presentation skills during the teaching and learning process and the acquisition of 21st - century skills, which are characterized by an increased competitive knowledge-based society due to changing nature and technological eruptions.

The current study also forms the basis for re-defining classroom practices in an attempt to enhance and transform nursing students’ learning experiences. This will cultivate the production of graduates nurses who will share their expertise and practical skills in the health care team by attending scientific conferences, clinical case presentations, and job interviews in the global health market. To achieve this, the study determined the baseline and end-line nursing students’ presentation skills during the preparation and presentation of classroom assignments using the traditional PowerPoint presentation and Pecha Kucha presentation format.

Methods and materials

This study was conducted in health training institutions in Tanzania. Tanzania has a total of 47 registered public and private universities and university colleges that offer health programs ranging from certificate to doctorate degrees [ 24 , 25 ]. A total of seven [ 7 ] out of 47 universities offer a bachelor of science in nursing, and four [ 4 ] universities offer master’s to doctorate degree programs in nursing and midwifery sciences [ 24 , 26 ]. To enhance the representation of nursing students in Tanzania, this study was conducted in Dodoma Municipal Council, which is one of Tanzania’s 30 administrative regions [ 33 ]. Dodoma Region has two [ 2 ] universities that offer nursing programs at diploma and degree levels [ 34 ]. The referred universities host a large number of nursing students compared to the other five [ 5 ] universities in Tanzania, with traditional students’ presentation approaches predominating nursing students’ teaching and learning processes [ 7 , 32 , 35 ].

The two universities under study include the University of Dodoma and St. John’s University of Tanzania, which are located in Dodoma Urban District. The University of Dodoma is a public university that provides 142 training programs at the diploma, bachelor degree, and master’s degree levels with about 28,225 undergraduate students and 724 postgraduate students [ 26 , 27 ]. The University of Dodoma also has 1,031 nursing students pursuing a Bachelor of Science in Nursing and 335 nursing students pursuing a Diploma in Nursing in the academic year 2022–2023 [ 33 ]. The St. John’s University of Tanzania is a non-profit private university that is legally connected with the Christian-Anglican Church [ 36 ]. It has student enrollment ranging from 5000 to 5999 and it provides training programs leading to higher education degrees in a variety of fields, including diplomas, bachelor degrees, and master’s degrees [ 37 ]. It hosts 766 nursing students pursuing a Bachelor of Science in Nursing and 113 nursing students pursuing a Diploma in Nursing in the academic year 2022–2023 [ 30 , 31 ].

Study design and approach

An uncontrolled quasi-experimental design with a quantitative research approach was used to establish quantifiable data on the participants’ socio-demographic profiles and outcome variables under study. The design involved pre- and post-tests to determine the effects of the intervention on the aforementioned outcome variable. The design involved three phases, namely the baseline data collection process (pre-test via a cross-sectional survey), implementation of the intervention (process), and end-line assessment (post-test), as shown in Fig.  1 [ 7 ].

A flow pattern of study design and approach

Target population

The study involved nursing students pursuing a Diploma in nursing and a bachelor of science in nursing in Tanzania. The population was highly expected to demonstrate competences and mastery of different survival and life skills in order to enable them to work independent at various levels of health facilities within and outside Tanzania. This cohort of undergraduate nursing students also involved adult learners who can set goals, develop strategies to achieve their goals, and hence achieve positive professional behavioral outcomes [ 7 ]. Moreover, as per annual data, the average number of graduate nursing students ranges from 3,500 to 4,000 from all colleges and universities in the country [ 38 ].

Study population

The study involved first- and third-year nursing students pursuing a Diploma in Nursing and first-, second-, and third-year nursing students pursuing a Bachelor of Science in Nursing at the University of Dodoma. The population had a large number of enrolled undergraduate nursing students, thus making it an ideal population for intervention, and it approximately served as a good representation of the universities offering nursing programs [ 11 , 29 ].

Inclusion criteria

The study included male and female nursing students pursuing a Diploma in nursing and a bachelor of science in nursing at the University of Dodoma. The referred students included those who were registered at the University of Dodoma during the time of study. Such students live on or off campus, and they were not exposed to PK training despite having regular classroom attendance. This enhanced enrollment of adequate study samples from each study program, monitoring of study intervention, and easy control of con-founders.

Exclusion criteria

All students recruited in the study were assessed at baseline, exposed to a training package and obtained their post-intervention learning experience. None of the study participants, who either dropped out of the study or failed to meet the recruitment criteria.

Sample size determination

A quasi-experimental study on Pecha Kucha as an alternative to traditional PowerPoint presentations at Worcester University, United States of America, reported significant student engagement during Pecha Kucha presentations compared with traditional PowerPoint presentations [ 29 ]. The mean score for the classroom with the traditional PowerPoint presentation was 2.63, while the mean score for the Pecha Kucha presentation was 4.08. This study adopted the formula that was used to calculate the required sample size for an uncontrolled quasi-experimental study among pre-scholars [ 39 ]. The formula is stated as:

Where: Zα was set at 1.96 from the normal distribution table.

Zβ was set at 0.80 power of the study.

Mean zero (π0) was the mean score of audiences’ engagement in using PowerPoint presentation = 2.63.

Mean one (π1) was the mean score of audience’s engagement in using Pecha Kucha presentation = 4.08.

Sampling technique

Given the availability of higher-training institutions in the study area that offer undergraduate nursing programs, a simple random sampling technique was used, whereby two cards, one labelled “University of Dodoma” and the other being labelled “St. Johns University of Tanzania,” were prepared and put in the first pot. The other two cards, one labelled “yes” to represent the study setting and the other being labelled “No” to represent the absence of study setting, were put in the second pot. Two research assistants were asked to select a card from each pot, and consequently, the University of Dodoma was selected as the study setting.

To obtain the target population, the study employed purposive sampling techniques to select the school of nursing and public health at the University of Dodoma. Upon arriving at the School of Nursing and Public Health of the University of Dodoma, the convenience sampling technique was employed to obtain the number of classes for undergraduate nursing students pursuing a Diploma in Nursing and a Bachelor of Science in Nursing. The study sample comprised the students who were available at the time of study. A total of five [ 5 ] classes of Diploma in Nursing first-, second-, and third-years and Bachelor of Science in Nursing first-, second-, and third-years were obtained.

To establish the representation for a minimum sample from each class, the number of students by sex was obtained from each classroom list using the proportionate stratified sampling technique (sample size/population size× stratum size) as recommended by scholars [ 40 ]. To recruit the required sample size from each class by gender, a simple random sampling technique through the lottery method was employed to obtain the required sample size from each stratum. During this phase, the student lists by gender from each class were obtained, and cards with code numbers, which were mixed with empty cards depending on the strata size, were allocated for each class and strata. Both labeled and empty cards were put into different pots, which were labeled appropriately by their class and strata names. Upon arriving at the specific classroom and after the introduction, the research assistant asked each nursing student to pick one card from the respective strata pot. Those who selected cards with code numbers were recruited in the study with their code numbers as their participation identity numbers. The process continued for each class until the required sample size was obtained.

To ensure the effective participation of nursing students in the study, the research assistant worked hand in hand with the facilitators and lecturers of the respective classrooms, the head of the department, and class representatives. The importance, advantages, and disadvantages of participating in the study were given to study participants during the recruitment process in order to create awareness and remove possible fears. During the intervention, study participants were also given pens and notebooks in an attempt to enable them to take notes. Moreover, the bites were provided during the training sessions. The number of participants from each classroom and the sampling process are shown in Fig.  2 [ 7 ].

Flow pattern of participants sampling procedures

Data collection tools

The study adapted and modified the students’ questionnaire on presentation skills from scholars [ 20 , 23 , 26 , 27 , 28 , 29 ]. The modification involved rephrasing the question statement, breaking down items into specific questions, deleting repeated items that were found to measure the same variables, and improving language to meet the literacy level and cultural norms of study participants.

The data collection tool consisted of 68 question items that assessed the socio-demographic characteristics of the study participants and 33 question items rated on a five-point Likert scale, which ranges from 5 = strongly agree, 4 = agree, 3 = not sure, 2 = disagree, and 1 = strongly disagree. The referred tool was used to assess the students’ skills during the preparation and presentation of the assignments using the traditional PowerPoint presentation and Pecha Kucha presentation formats.

The students’ assessment specifically focused on the students’ ability to prepare the presentation content, master the learning content, share presentation materials, and communicate their understanding to audiences in the classroom context.

Validity and reliability of research instruments

Validity of the research instrument refers to whether the instrument measures the behaviors or qualities that are intended to be measured, and it is a measure of how well the measuring instrument performs its function [ 41 ]. The structured questionnaire, which intends to assess the participants’ presentation skills was validated for face and content validity. The principal investigator initially adapted the question items for different domains of students’ learning when preparing and presenting their assignment in the classroom.

The items were shared and discussed by two [ 2 ] educationists, two [ 2 ] research experts, one [ 1 ] statistician, and supervisors in order to ensure clarity, appropriateness, adequacy, and coverage of the presentation skills using Pecha Kucha presentation format. The content validity test was used until the saturation of experts’ opinions and inputs was achieved. The inter-observer rating scale on a five-point Likert scale ranging from 5-points = very relevant to 1-point = not relevant was also used.

The process involved addition, input deletion, correction, and editing for relevance, appropriateness, and scope of the content for the study participants. Some of the question items were broken down into more specific questions, and new domains evolved. Other question items that were found to measure the same variables were also deleted to ease the data collection and analysis. Moreover, the grammar and language issues were improved for clarity based on the literacy level of the study participants.

Reliability of the research instruments refers to the ability of the research instruments or tools to provide similar and consistent results when applied at different times and circumstances [ 41 ]. This study adapted the tools and question items used by different scholars to assess the impact of PKP on student learning [ 12 , 15 , 18 ].

To ensure the reliability of the tools, a pilot study was conducted in one of the nursing training institutions in order to assess the complexity, readability, clarity, completeness, length, and duration of the tool. Ambiguous and difficult (left unanswered) items were modified or deleted based on the consensus that was reached with the consulted experts and supervisor before subjecting the questionnaires to a pre-test.

The study involved 10% of undergraduate nursing students from an independent geographical location for a pilot study. The findings from the pilot study were subjected to explanatory factor analysis (Set a ≥ 0.3) and scale analysis in order to determine the internal consistency of the tools using the Cronbach alpha of ≥ 0.7, which was considered reliable [ 42 , 43 , 44 ]. Furthermore, after the data collection, the scale analysis was computed in an attempt to assess their internal consistency using SPPSS version 26, whereby the Cronbach alpha for question items that assessed the participants’ presentation skills was 0.965.

Data collection method

The study used the researcher-administered questionnaire to collect the participants’ socio-demographic information, co-related factors, and presentation skills as nursing students prepare and present their assignments in the classroom. This enhanced the clarity and participants’ understanding of all question items before providing the appropriate responses. The data were collected by the research assistants in the classroom with the study participants sitting distantly to ensure privacy, confidentiality, and the quality of the information that was provided by the research participants. The research assistant guided and led the study participants to answer the questions and fill in information in the questionnaire for each section, domain, and question item. The research assistant also collected the baseline information (pre-test) before the intervention, which was then compared with the post-intervention information. This was done in the first week of June 2023, after training and orientation of the research assistant on the data collection tools and recruitment of the study participants.

Using the researcher-administered questionnaire, the research assistant also collected the participants’ information related to presentation skills as they prepared and presented their given assignments after the intervention during the second week of July 2023. The participants submitted their presentations to the principle investigator and research assistant to assess the organization, visual appeal and creativity, content knowledge, and adherence to Pecha Kucha presentation requirements. Furthermore, the evaluation of the participants’ ability to share and communicate the given assignment was observed in the classroom presentation using the Pecha Kucha presentation format.

Definitions of variables

Pecha kucha presentation.

It refers to a specific style of presentation whereby the presenter delivers the content using 20 slides that are dominated by images, pictures, tables, or figures. Each slide is displayed for 20 s, thus making a total of 400 s (6 min and 40 s) for the whole presentation.

Presentation skills in this study

This involved students’ ability to plan, prepare, master learning content, create presentation materials, and share them with peers or the audience in the classroom. They constitute the learning activities that stimulate creativity, innovation, critical thinking, and problem-solving skills.

Measurement of pecha kucha preparation and presentation skills

The students’ presentation skills were measured using the four [ 4 ] learning domains. The first domain constituted the students’ ability to plan and prepare the presentation content. It consisted of 17 question items that assessed the students’ ability to gather and select information, search for specific content to be presented in the classroom, find out the learning content from different resources, and search for literature materials for the preparation of the assignment using traditional PowerPoint presentations and Pecha Kucha formats. It also aimed to ascertain a deeper understanding of the contents or topic, learning ownership and motivation to learn the topics with clear understanding and the ability to identify the relevant audience, segregate, and remove unnecessary contents using the Pecha Kucha format.

The second domain constituted the students’ mastery of learning during the preparation and presentation of their assignment before the audience in the classroom. It consisted of six [ 6 ] question items that measured the students’ ability to read several times, rehearse before the classroom presentation, and practice the assignment and presentation harder. It also measures the students’ ability to evaluate the selected information and content before their actual presentation and make revisions to the selected information and content before the presentation using the Pecha Kucha format.

The third domain constituted the students’ ability to prepare the presentation materials. It consisted of six [ 6 ] question items that measured the students’ ability to organize the information and contents, prepare the classroom presentation, revise and edit presentation resources, materials, and contents, and think about the audience and classroom design. The fourth domain constituted the students’ ability to share their learning. It consisted of four [ 4 ] question items that measured the students’ ability to communicate their learning with the audience, present a new understanding to the audience, transfer the learning to the audience, and answer the questions about the topic or assignment given. The variable was measured using a 5-point Likert scale. The average scores were computed for each domain, and an overall mean score was calculated across all domains. Additionally, an encompassing skills score was derived from the cumulative scores of all four domains, thus providing a comprehensive evaluation of the overall skills level.

Implementation of intervention

The implementation of the study involved the training of research assistants, sampling of the study participants, setting of the venue, pre-assessment of the students’ presentation skills using traditional PowerPoint presentations, training and demonstration of Pecha Kucha presentations to study participants, and assigning the topics to study participants. The implementation of the study also involved the participants’ submission of their assignments to the Principal Investigator for evaluation, the participants’ presentation of their assigned topic using the Pecha Kucha format, post-intervention assessment of the students’ presentation skills, data analysis, and reporting [ 7 ]. The intervention involved Principal Investigator and two [ 2 ] trained research assistants. The intervention in question was based on the concept of multimedia theory of cognitive learning (MTCL) for enhancing effective leaning in 21st century.

Training of research assistants

Two research assistants were trained with regard to the principles, characteristics, and format of Pecha Kucha presentations using the curriculum from the official Pecha Kucha website. Also, research assistants were oriented to the data collection tools and methods in an attempt to guarantee the relevancy and appropriate collection of the participants’ information.

Schedule and duration of training among research assistants

The PI prepared the training schedule and venue after negotiation and consensus with the research assistants. Moreover, the Principle Investigator trained the research assistants to assess the learning, learn how to collect the data using the questionnaire, and maintain the privacy and confidentiality of the study participants.

Descriptions of interventions

The intervention was conducted among the nursing students at the University of Dodoma, which is located in Dodoma Region, Tanzania Mainland, after obtaining their consent. The participants were trained regarding the concepts, principles, and characteristics of Pecha Kucha presentations and how to prepare and present their assignments using the Pecha Kucha presentation format. The study participants were also trained regarding the advantages and disadvantages of Pecha Kucha presentations. The training was accompanied by one example of an ideal Pecha Kucha presentation on the concepts of pressure ulcers. The teaching methods included lecturing, brainstorming, and small group discussion. After the training session, the evaluation was conducted to assess the participants’ understanding of the Pecha Kucha conceptualization, its characteristics, and its principles.

Each participant was given a topic as an assignment from the fundamentals of nursing, medical nursing, surgical nursing, community health nursing, mental health nursing, emergency critical care, pediatric, reproductive, and child health, midwifery, communicable diseases, non-communicable diseases, orthopedics and cross-cutting issues in nursing as recommended by scholars [ 21 , 38 ]. The study participants were given 14 days for preparation, rehearsal of their presentation using the Pecha Kucha presentation format, and submission of the prepared slides to the research assistant and principle investigator for evaluation and arrangement before the actual classroom presentation. The evaluation of the participants’ assignments involved the number of slides, quality of images used, number of words, organization of content and messages to be delivered, slide transition, duration of presentation, flow, and organization of slides.

Afterwards, each participant was given 6 min and 40 s for the presentation and 5 min to 10 min for answering the questions on the topic presented as raised by other participants. An average of 4 participants obtained the opportunity to present their assignments in the classroom every hour. After the completion of all presentations, the research assistants assessed the participant’s presentation skills using the researcher-administered questionnaire. The collected data were entered in SPSS version 26 and analyzed in an attempt to compare the mean score of participants’ presentation skills with the baseline mean score. The intervention sessions were conducted in the selected classrooms, which were able to accommodate all participants at the time that was arranged by the participant’s coordinators, institution administrators, and subject facilitators of the University of Dodoma, as described in Table  1 [ 7 ].

Evaluation of intervention

During the classroom presentation, there were 5 to 10 min for classroom discussion and reflection on the content presented, which was guided by the research assistant. During this time, the participants were given the opportunity to ask the questions, get clarification from the presenter, and provide their opinion on how the instructional messages were presented, content coverage, areas of strength and weakness for improvement, and academic growth. After the completion of the presentation sessions, the research assistant provided the questionnaire to participants in order to determine their presentation skills during the preparation of their assignments and classroom presentations using the Pecha Kucha presentation format.

Data analysis

The findings from this study were analyzed using the Statistical Package for Social Science (SPSS) computer software program version 26. The percentages, frequencies, frequency distributions, means, standard deviations, skewness, and kurtosis were calculated, and the results were presented using the figures, tables, and graphs. The mean score analysis was computed, and descriptive statistical analysis was used to analyze the demographic information of the participants in an attempt to determine the frequencies, percentages, and mean scores of their distributions. A paired sample t-test was used to compare the mean score differences of the presentation skills within the groups before and after the intervention. The mean score differences were determined based on the baseline scores against the post-intervention scores in order to establish any change in terms of presentation skills among the study participants.

The association between the Pecha Kucha presentation and the development of participants’ presentation skills was established using linear regression analysis set at a 95% confidence interval and 5% (≤ 0.05) significance level in an attempt to accept or reject the null hypothesis.

However, N-1 dummy variables were formed for the categorical independent variables so as to run the linear regression for the factors associated with the presentation skills. The linear regression equation with dummy variables is presented as follows:

Β 0 is the intercept.

Β 1 , Β 2 , …. Β k-1 are the coefficients which correspond to the dummy variables representing the levels of X 1 .

Β k is the coefficient which corresponds to the dummy variable representing the levels of X 2 .

Β k+1 is the coefficient which corresponds to the continuous predictor X 3 .

X 1,1 , X 1,2 ,……. X 1,k-1 are the dummy variables corresponding to the different levels of X 1 .

ε represents the error term.

The coefficients B1, B2… Bk indicate the change in the expected value of Y for each category relative to the reference category. If the Beta estimate is positive for the categorical or dummy variables, it means that the corresponding covariate has a positive impact on the outcome variable compared to reference category. However, if the beta estimate is positive for the case of continuous covariates, it means that the corresponding covariate has direct proportion effect on the outcome variables.

The distribution of the outcome variables was approximately normally distributed since the normality of the data is one of the requirements for parametric analysis. A paired t test was performed to compare the presentation skills of nursing students before and after the intervention.

Social-demographic characteristics of the study participants

The study involved a total of 230 nursing students, of whom 151 (65.65%) were male and the rest were female. The mean age of study participants was 23.03 ± 2.69, with the minimum age being 19 and the maximum age being 37. The total of 163 (70.87%) students, which comprised a large proportion of respondents, were aged less than or equal to 23, 215 (93.48%) participants were living on campus, and 216 (93.91) participants were exposed to social media.

A large number of study participants (82.17%) were pursuing a bachelor of Science in Nursing, with the majority being first-year students (30.87%). The total of 213 (92.61%) study participants had Form Six education as their entry qualification, with 176 (76.52%) participants being the product of public secondary schools and interested in the nursing profession. Lastly, the total of 121 (52.61%) study participants had never been exposed to any presentation training; 215 (93.48%) students had access to individual classroom presentations; and 227 (98.70%) study participants had access to group presentations during their learning process. The detailed findings for the participants’ social demographic information are indicated in Table  2 [ 46 ].

Baseline nursing students’ presentation skills using traditional powerPoint presentations

The current study assessed the participant’s presentation skills when preparing and presenting the materials before the audience using traditional PowerPoint presentations. The study revealed that the overall mean score of the participants’ presentation skills was 4.07 ± 0.56, including a mean score of 3.98 ± 0.62 for the participants’ presentation skills during the preparation of presentation content before the classroom presentation and a mean score of 4.18 ± 0.78 for the participants’ mastery of learning content before the classroom presentation. Moreover, the study revealed a mean score of 4.07 ± 0.71 for participants’ ability to prepare presentation materials for classroom presentations and a mean score of 4.04 ± 0.76 for participants’ ability to share the presentation materials in the classroom, as indicated in Table  3 [ 46 ].

Factors Associated with participants’ presentation skills through traditional powerPoint presentation

The current study revealed that the participants’ study program has a significant effect on their presentation skills, whereby being the bachelor of science in nursing was associated with a 0.37561 (P value < 0.027) increase in the participants’ presentation skills.The year of study also had significant effects on the participants’ presentation skills, whereby being a second-year bachelor student was associated with a 0.34771 (P value < 0.0022) increase in the participants’ presentation skills compared to first-year bachelor students and diploma students. Depending on loans as a source of student income retards presentation skills by 0.24663 (P value < 0.0272) compared to those who do not depend on loans as the source of income. Furthermore, exposure to individual presentations has significant effects on the participants’ presentation skills, whereby obtaining an opportunity for individual presentations was associated with a 0.33732 (P value 0.0272) increase in presentation skills through traditional PowerPoint presentations as shown in Table  4 [ 46 ].

Nursing student presentation skills through pecha kucha presentations

The current study assessed the participant’s presentation skills when preparing and presenting the materials before the audience using Pecha Kucha presentations. The study revealed that the overall mean score and standard deviation of participants’ presentation skills using the Pecha Kucha presentation format were 4.54 ± 0.59, including a mean score of 4.49 ± 0.66 for participant’s presentation skills during preparation of the content before classroom presentation and a mean score of 4.58 ± 0.65 for participants’ mastery of learning content before classroom presentation. Moreover, the study revealed a mean score of 4.58 ± 0.67 for participants ability to prepare the presentation materials for classroom presentation and a mean score of 4.51 ± 0.72 for participants ability to share the presentation materials in the classroom using Pecha Kucha presentation format as indicated in Table  5 [ 46 ].

Comparing Mean scores of participants’ presentation skills between traditional PowerPoint presentation and pecha kucha Presentation

The current study computed a paired t-test to compare and determine the mean change, effect size, and significance associated with the participants’ presentation skills when using the traditional PowerPoint presentation and Pecha Kucha presentation formats. The study revealed that the mean score of the participants’ presentation skills through the Pecha Kucha presentation was 4.54 ± 0.59 (p value < 0.0001) compared to the mean score of 4.07 ± 0.56 for the participants’ presentation skills using the traditional power point presentation with an effect change of 0.78. With regard to the presentation skills during the preparation of presentation content before the classroom presentation, the mean score was 4.49 ± 0.66 using the Pecha Kucha presentation compared to the mean score of 3.98 ± 0.62 for the traditional PowerPoint presentation. Its mean change was 0.51 ± 0.84 ( p  < .0001) with an effect size of 0.61.

Regarding the participants’ mastery of learning content before the classroom presentation, the mean score was 4.58 ± 0.65 when using the Pecha Kucha presentation format, compared to the mean score of 4.18 ± 0.78 when using the traditional power point presentation. Its mean change was 0.40 ± 0.27 ( p  < .0001) with an effect size of 1.48. Regarding the ability of the participants to prepare the presentation materials for classroom presentations, the mean score was 4.58 ± 0.67 when using the Pecha Kucha presentation format, compared to 4.07 ± 0.71 when using the traditional PowerPoint presentation. Its mean change was 0.51 ± 0.96 ( p  < .0001) with an effect size of 0.53.

Regarding the participants’ presentation skills when sharing the presentation material in the classroom, the mean score was 4.51 ± 0.72 when using the Pecha Kucha presentation format, compared to 4.04 ± 0.76 when using the traditional PowerPoint presentations. Its mean change was 0.47 ± 0.10, with a large effect size of 4.7. Therefore, Pecha Kucha presentation pedagogy has a significant effect on the participants’ presentation skills than the traditional PowerPoint presentation as shown in Table  6 [ 46 ].

Factors associated with presentation skills among nursing students through pecha kucha presentation

The current study revealed that the participant’s presentation skills using the Pecha Kucha presentation format were significantly associated with knowledge of the Pecha Kucha presentation format, whereby increase in knowledge was associated with a 0.0239 ( p  < .0001) increase in presentation skills. Moreover, the current study revealed that the presentation through the Pecha Kucha presentation format was not influenced by the year of study, whereby being a second-year student could retard the presentation skills by 0.23093 (p 0.039) compared to a traditional PowerPoint presentation. Other factors are shown in Table  7 [ 46 ].

Social-demographic characteristics profiles of participants

The proportion of male participants was larger than the proportion of female participants in the current study. This was attributable to the distribution of sex across the nursing students at the university understudy, whose number of male nursing students enrolled was higher than female students. This demonstrates the high rate of male nursing students’ enrolment in higher training institutions to pursue nursing and midwifery education programs. Different from the previous years, the nursing training institutions were predominantly comprised of female students and female nurses in different settings. This significant increase in male nursing students’ enrollment in nursing training institutions predicts a significant increase in the male nursing workforce in the future in different settings.

These findings on Pecha Kucha as an alternative to PowerPoint presentations in Massachusetts, where the proportion of female participants was large as compared to male participants, are different from the experimental study among English language students [ 29 ]. The referred findings are different from the results of the randomized control study among the nursing students in Anakara, Turkey, where a large proportion of participants were female nursing students [ 47 ]. This difference in participants’ sex may be associated with the difference in socio-cultural beliefs of the study settings, country’s socio-economic status, which influence the participants to join the nursing profession on the basis of securing employment easily, an opportunity abroad, or pressure from peers and parents. Nevertheless, such differences account for the decreased stereotypes towards male nurses in the community and the better performance of male students in science subjects compared to female students in the country.

The mean age of the study participants was predominantly young adults with advanced secondary education. Their ages reflect adherence to national education policy by considering the appropriate age of enrollment of the pupils in primary and secondary schools, which comprise the industries for students at higher training institutions. This age range of the participants in the current study suits the cognitive capability expected from the participants in order to demonstrate different survival and life skills by being able to set learning goals and develop strategies to achieve their goals according to Jean Piaget’s theory of cognitive learning [ 41 , 42 ].

Similar age groups were noted in the study among nursing students in a randomized control study in Anakara Turkey where the average age was 19.05 ± 0.2 [ 47 ]. A similar age group was also found in a randomized control study among liberal arts students in Anakara, Turkey, on differences in instructor, presenter, and audience ratings of Pecha Kucha presentations and traditional student presentations where the ages of the participants ranged between 19 and 22 years [ 49 ].

Lastly, a large proportion of the study participants had the opportunity for individual and group presentations in the classroom despite having not been exposed to any presentation training before. This implies that the teaching and learning process in a nursing education program is participatory and student-centered, thus giving the students the opportunity to interact with learning contents, peers, experts, webpages, and other learning resources to become knowledgeable. These findings fit with the principle that guides and facilitates the student’s learning from peers and teachers according to the constructivism theory of learning by Lev Vygotsky [ 48 ].

Effects of pecha kucha presentation pedagogy on participants’ presentation skills

The participants’ presentation skills were higher for Pecha Kucha presentations compared with traditional PowerPoint presentations. This display of the Pecha Kucha presentation style enables the nursing students to prepare the learning content, master their learning content before classroom presentations, create good presentation materials and present the materials, before the audience in the classroom. This finding was similar to that at Padang State University, Indonesia, among first-year English and literature students whereby the Pecha Kucha Presentation format helped the students improve their skills in presentation [ 20 ]. Pecha Kucha was also found to facilitate careful selection of the topic, organization and outlining of the students’ ideas, selection of appropriate images, preparation of presentations, rehearsing, and delivery of the presentations before the audience in a qualitative study among English language students at the Private University of Manila, Philippines [ 23 ].

The current study found that Pecha Kucha presentations enable the students to perform literature searches from different webpages, journals, and books in an attempt to identify specific contents during the preparation of the classroom presentations more than traditional PowerPoint presentations. This is triggered by the ability of the presentation format to force the students to filter relevant and specific information to be included in the presentation and search for appropriate images, pictures, or figures to be presented before the audience. Pecha Kucha presentations were found to increase the ability to perform literature searches before classroom presentations compared to traditional PowerPoint presentations in an experimental study among English language students at Worcester State University [ 29 ].

The current study revealed that Pecha Kucha presentations enable the students to create a well-structured classroom presentation effectively by designing 20 meaningful and content-rich slides containing 20 images, pictures, or figures and a transitional flow of 20 s for each slide, more than the traditional PowerPoint presentation with an unlimited number of slides containing bullets with many texts or words. Similarly, in a cross-sectional study of medical students in India, Pecha Kucha presentations were found to help undergraduate first-year medical students learn how to organize knowledge in a sequential fashion [ 26 ].

The current study revealed that Pecha Kucha presentations enhance sound mastery of the learning contents and presentation materials before the classroom presentation compared with traditional PowerPoint presentations. This is hastened by the fact that there is no slide reading during the classroom Pecha Kucha presentation, thus forcing students to read several times, rehearse, and practice harder the presentation contents and materials before the classroom presentation. Pecha Kucha presentation needed first year English and literature students to practice a lot before their classroom presentation in a descriptive qualitative study at Padang State University-Indonesia [ 20 ].

The current study revealed that the participants became more confident in answering the questions about the topic during the classroom presentation using the Pecha Kucha presentation style than during the classroom presentation using the tradition PowerPoint presentation. This is precipitated by the mastery level of the presentation contents and materials through rehearsal, re-reading, and material synthesis before the classroom presentations. Moreover, Pecha Kucha was found to significantly increase the students’ confidence during classroom presentation and preparation in a qualitative study among English language students at the Private University of Manila, Philippines [ 23 ].

Hence, there was enough evidence to reject the null hypothesis in that there was no significant difference in nursing students’ presentation skills between the baseline and end line. The Pecha Kucha presentation format has a significant effect on nursing student’s classroom presentation skills as it enables them to prepare the learning content, have good mastery of the learning contents, create presentation materials, and confidently share their learning with the audience in the classroom.

The current study’s findings complement the available pieces of evidence on the effects of Pecha Kucha presentations on the students’ learning and development of survival life skills in the 21st century. Pecha kucha presentations have more significant effects on the students’ presentation skills compared with traditional PowerPoint presentations. It enables the students to select the topic carefully, organize and outline the presentation ideas, select appropriate images, create presentations, rehearse the presentations, and deliver them confidently before an audience. It also enables the students to select and organize the learning contents for classroom presentations more than traditional PowerPoint presentations.

Pecha Kucha presentations enhance the mastery of learning content by encouraging the students to read the content several times, rehearse, and practice hard before the actual classroom presentation. It increases the students’ ability to perform literature searches before the classroom presentation compared to a traditional PowerPoint presentation. Pecha Kucha presentations enable the students to create well-structured classroom presentations more effectively compared to traditional PowerPoint presentations. Furthermore, Pecha Kucha presentations make the students confident during the presentation of their assignments and project works before the audience and during answering the questions.

Lastly, Pecha Kucha presentations enhance creativity among the students by providing the opportunity for them to decide on the learning content to be presented. Specifically, they are able to select the learning content, appropriate images, pictures, or figures, organize and structure the presentation slides into a meaningful and transitional flow of ideas, rehearse and practice individually before the actual classroom presentation.

Strength of the study

This study has addressed the pedagogical gap in nursing training and education by providing new insights on the innovative students’ presentation format that engages students actively in their learning to bring about meaningful and effective students’ learning. It has also managed to recruit, asses, and provide intended intervention to 230 nursing students without dropout.

Study limitation

The current study has pointed out some of the strengths of the PechaKucha presentations on the students’ presentation skills over the traditional students’ presentations. However, the study had the following limitations: It involved one group of nursing students from one of the public training institutions in Tanzania. The use of one university may obscure the interpretation of the effects of the size of the intervention on the outcome variables of interest, thus limiting the generalization of the study findings to all training institutions in Tanzania. Therefore, the findings from this study need to be interpreted by considering this limitation. The use of one group of nursing students from one university to explore their learning experience through different presentation formats may also limit the generalization of the study findings to all nursing students in the country. The limited generalization may be attributed to differences in socio-demographic characteristics, learning environments, and teaching and learning approaches. Therefore, the findings from this study need to be interpreted by considering this limitation.

Suggestions for future research

The future research should try to overcome the current study limitations and shortcomings and extend the areas assessed by the study to different study settings and different characteristics of nursing students in Tanzania as follows: To test rigorously the effects of Pecha Kucha presentations in enhancing the nursing students’ learning, the future studies should involve nursing students’ different health training institutions rather than one training institution. Future studies should better use the control students by randomly allocating the nursing students or training institutions in the intervention group or control group in order to assess the students’ learning experiences through the use of Pecha Kucha presentations and PowerPoint presentations consecutively. Lastly, future studies should focus on nursing students’ mastery of content knowledge and students’ classroom performance through the use of the Pecha Kucha presentation format in the teaching and learning process.

Data availability

The datasets generated and analyzed by this study can be obtained from the corresponding author on reasonable request through [email protected] & [email protected].

Abbreviations

Doctor (PhD)

Multimedia Theory of Cognitive Learning

National Council for Technical and Vocational Education and Training

Principle Investigator

Pecha Kucha presentation

Statistical Package for Social Sciences

Tanzania Commission for Universities

World Health Organization

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Acknowledgements

The supervisors at the University of Dodoma, statisticians, my employer, family members, research assistants and postgraduate colleagues are acknowledged for their support in an attempt to facilitate the development and completion of this manuscript.

The source of funds to conduct this study was the registrar, Tanzania Nursing and Midwifery Council (TNMC) who is the employer of the corresponding author. The funds helped the author in developing the protocol, printing the questionnaires, and facilitating communication during the data collection and data analysis and manuscript preparation.

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S.J.H: conceptualization, proposal development, data collection, data entry, data cleaning and analysis, writing the original draft of the manuscript W.C.M: Conceptualization, supervision, review, and editing of the proposal, and the final manuscript S.S.A: Conceptualization, supervision, review, and editing of the proposal and the final manuscript.

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Haramba, S.J., Millanzi, W.C. & Seif, S.A. Effects of pecha kucha presentation pedagogy on nursing students’ presentation skills: a quasi-experimental study in Tanzania. BMC Med Educ 24 , 952 (2024). https://doi.org/10.1186/s12909-024-05920-2

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Facility for Rare Isotope Beams

At michigan state university, user community focuses on the future of the field and fostering a diverse and equitable workforce.

The 2024 Low Energy Community Meeting (LECM) took place 7-9 August on the campus of the University of Tennessee Knoxville. LECM brings together members of the worldwide low-energy nuclear physics community to interact and discuss future plans, initiatives, and instruments. Over the course of the three days, 250 participants attended the meeting from 65 institutions and eight countries.

The LECM organizing committee includes representatives from FRIB, Argonne National Laboratory (ANL), the Association for Research at University Nuclear Accelerators (ARUNA), the Argonne Tandem Linac Accelerator System (ATLAS), the Center for Nuclear Astrophysics across Messengers (CeNAM), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL), the FRIB Theory Alliance (FRIB-TA), and the FRIB Users Organization Executive Committee. FRIB hosted the meeting last year, and ORNL hosted this year. Texas A&M University will host next year.

LECM included plenary sessions, four working group sessions, and four workshops: Modular Neutron Array (MoNA) collaboration, Fission studies with rare isotope beams, early careers, and public engagement. 

The LECM plenary sessions featured presentations from the FRIB Achievement Awards for Early Career Researchers; a presentation on diversity and inclusion; Kairos Power’s Hermes demonstration reactor; and comments from representatives from the Department of Energy and the National Science Foundation. The meeting highlighted the status at major user facilities—FRIB, ATLAS, and ARUNA.

The 2024 LECM affirmation and resolutions stated:

Affirmation: Our community affirms in the strongest possible terms its commitment to foster a diverse and equitable workforce and to support and respect diversity in all its forms. Individually and collectively we commit to ensuring an inclusive and accessible environment for all and taking action if these values are not being upheld.

Resolution 1: The highest priority for low-energy nuclear physics and nuclear astrophysics research is to maintain U.S. world leadership in nuclear science by capitalizing on recent investments. To this end, we strongly support: 

• Robust theoretical and experimental research programs and the development and retention of a diverse and equitable workforce; 
• The optimal operation of the FRIB and ATLAS national user facilities;
• Investments in the ARUNA facilities, and key national laboratory facilities; 
• The FRIB Theory Alliance and all its initiatives.

All are critical to fully realize the scientific potential of the field and foster future breakthroughs.

Resolution 2: The science case for an energy upgrade of FRIB to 400 MeV/u is compelling. FRIB400 greatly expands the opportunities in the field. We strongly endorse starting the upgrade during the upcoming Long Range Plan period to harness its significant discovery potential. We support instrument developments, including the FDS and ISLA, now that GRETA and HRS are underway. These community devices are important to realize the full scope of scientific opportunities

Resolution 3: Computing is essential to advance all fields of nuclear science. We strongly support enhancing opportunities in computational nuclear science to accelerate discoveries and maintain U.S. leadership by: 

• Strengthening programs and partnerships to ensure the efficient utilization of new high-performance computing (HPC) hardware and new capabilities and approaches offered by artificial intelligence/machine learning (AI/ML) and quantum computing (QC); 
• Establishing programs that support the education, training of, and professional pathways for a diverse and multidisciplinary workforce with cross-disciplinary collaborations in HPC, AI/ML, and QC; 
• Expanding access to dedicated hardware and resources for HPC and new emerging computational technologies, as well as capacity computing essential for many research efforts.

Resolution 4: Research centers are important for low-energy nuclear science. They facilitate strong national and international communications and collaborations across disciplines and across theory and experiment. Interdisciplinary centers are particularly essential for nuclear astrophysics to seize new scientific opportunities in this area. We strongly endorse a nuclear astrophysics center that builds on the success of JINA, fulfills this vital role, and propels innovation in the multi-messenger era.

Resolution 5: Nuclear data play an essential role in all facets of nuclear science. Access to reliable, complete and up-to-date nuclear structure and reaction data is crucial for the fundamental nuclear physics research enterprise, as well as for the successes of applied missions in the areas of defense and security, nuclear energy, space exploration, isotope production, and medical applications. It is thus imperative to maintain an effective US role in the stewardship of nuclear data. 

• We endorse support for the compilation, evaluation, dissemination and preservation of nuclear data and efforts to build a diverse, equitable and inclusive workforce that maintains reliable and up-to-date nuclear databases through national and international partnerships. 
• We recommend prioritizing opportunities that enhance the prompt availability and quality of nuclear data and its utility for propelling scientific progress in nuclear structure, reactions and astrophysics and other fundamental physics research programs.
• We endorse identifying interagency-supported crosscutting opportunities for nuclear data with other programs, that enrich the utility of nuclear data in both science and society.

The community also presented a statement on isotopes and applications:

Applied Nuclear Science offers many tangible benefits to the United States and to the world. The Low Energy Nuclear Physics Community recognizes the societal importance of applied research, and strongly encourages support for this exciting and growing field with funding and beam time allocations that enable critical discovery science that will improve our lives and make us all safer.

Rare isotopes are necessary for research and innovation and must be available.  

10 Methods of Data Presentation That Really Work in 2024

Leah Nguyen • 20 August, 2024 • 13 min read

Have you ever presented a data report to your boss/coworkers/teachers thinking it was super dope like you’re some cyber hacker living in the Matrix, but all they saw was a pile of static numbers that seemed pointless and didn't make sense to them?

Understanding digits is rigid . Making people from non-analytical backgrounds understand those digits is even more challenging.

How can you clear up those confusing numbers and make your presentation as clear as the day? Let's check out these best ways to present data. 💎

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Data Presentation - What Is It?

The term ’data presentation’ relates to the way you present data in a way that makes even the most clueless person in the room understand. 

Some say it’s witchcraft (you’re manipulating the numbers in some ways), but we’ll just say it’s the power of turning dry, hard numbers or digits into a visual showcase that is easy for people to digest.

Presenting data correctly can help your audience understand complicated processes, identify trends, and instantly pinpoint whatever is going on without exhausting their brains.

Good data presentation helps…

• Make informed decisions and arrive at positive outcomes . If you see the sales of your product steadily increase throughout the years, it’s best to keep milking it or start turning it into a bunch of spin-offs (shoutout to Star Wars👀).
• Reduce the time spent processing data . Humans can digest information graphically 60,000 times faster than in the form of text. Grant them the power of skimming through a decade of data in minutes with some extra spicy graphs and charts.
• Communicate the results clearly . Data does not lie. They’re based on factual evidence and therefore if anyone keeps whining that you might be wrong, slap them with some hard data to keep their mouths shut.
• Add to or expand the current research . You can see what areas need improvement, as well as what details often go unnoticed while surfing through those little lines, dots or icons that appear on the data board.

Methods of Data Presentation and Examples

Imagine you have a delicious pepperoni, extra-cheese pizza. You can decide to cut it into the classic 8 triangle slices, the party style 12 square slices, or get creative and abstract on those slices. 

There are various ways to cut a pizza and you get the same variety with how you present your data. In this section, we will bring you the 10 ways to slice a pizza - we mean to present your data - that will make your company’s most important asset as clear as day. Let's dive into 10 ways to present data efficiently.

#1 - Tabular 

Among various types of data presentation, tabular is the most fundamental method, with data presented in rows and columns. Excel or Google Sheets would qualify for the job. Nothing fancy.

This is an example of a tabular presentation of data on Google Sheets. Each row and column has an attribute (year, region, revenue, etc.), and you can do a custom format to see the change in revenue throughout the year.

When presenting data as text, all you do is write your findings down in paragraphs and bullet points, and that’s it. A piece of cake to you, a tough nut to crack for whoever has to go through all of the reading to get to the point.

• 65% of email users worldwide access their email via a mobile device.
• Emails that are optimised for mobile generate 15% higher click-through rates.
• 56% of brands using emojis in their email subject lines had a higher open rate.

(Source: CustomerThermometer )

All the above quotes present statistical information in textual form. Since not many people like going through a wall of texts, you’ll have to figure out another route when deciding to use this method, such as breaking the data down into short, clear statements, or even as catchy puns if you’ve got the time to think of them.

#3 - Pie chart

A pie chart (or a ‘donut chart’ if you stick a hole in the middle of it) is a circle divided into slices that show the relative sizes of data within a whole. If you’re using it to show percentages, make sure all the slices add up to 100%.

The pie chart is a familiar face at every party and is usually recognised by most people. However, one setback of using this method is our eyes sometimes can’t identify the differences in slices of a circle, and it’s nearly impossible to compare similar slices from two different pie charts, making them the villains in the eyes of data analysts.

#4 - Bar chart

The bar chart is a chart that presents a bunch of items from the same category, usually in the form of rectangular bars that are placed at an equal distance from each other. Their heights or lengths depict the values they represent.

They can be as simple as this:

Or more complex and detailed like this example of data presentation. Contributing to an effective statistic presentation, this one is a grouped bar chart that not only allows you to compare categories but also the groups within them as well.

#5 - Histogram

Similar in appearance to the bar chart but the rectangular bars in histograms don’t often have the gap like their counterparts.

Instead of measuring categories like weather preferences or favourite films as a bar chart does, a histogram only measures things that can be put into numbers.

Teachers can use presentation graphs like a histogram to see which score group most of the students fall into, like in this example above.

#6 - Line graph

Recordings to ways of displaying data, we shouldn't overlook the effectiveness of line graphs. Line graphs are represented by a group of data points joined together by a straight line. There can be one or more lines to compare how several related things change over time. 

On a line chart’s horizontal axis, you usually have text labels, dates or years, while the vertical axis usually represents the quantity (e.g.: budget, temperature or percentage).

#7 - Pictogram graph

A pictogram graph uses pictures or icons relating to the main topic to visualise a small dataset. The fun combination of colours and illustrations makes it a frequent use at schools.

Pictograms are a breath of fresh air if you want to stay away from the monotonous line chart or bar chart for a while. However, they can present a very limited amount of data and sometimes they are only there for displays and do not represent real statistics.

#8 - Radar chart

If presenting five or more variables in the form of a bar chart is too stuffy then you should try using a radar chart, which is one of the most creative ways to present data.

Radar charts show data in terms of how they compare to each other starting from the same point. Some also call them ‘spider charts’ because each aspect combined looks like a spider web.

Radar charts can be a great use for parents who’d like to compare their child’s grades with their peers to lower their self-esteem. You can see that each angular represents a subject with a score value ranging from 0 to 100. Each student’s score across 5 subjects is highlighted in a different colour.

If you think that this method of data presentation somehow feels familiar, then you’ve probably encountered one while playing Pokémon .

#9 - Heat map

A heat map represents data density in colours. The bigger the number, the more colour intensity that data will be represented.

Most US citizens would be familiar with this data presentation method in geography. For elections, many news outlets assign a specific colour code to a state, with blue representing one candidate and red representing the other. The shade of either blue or red in each state shows the strength of the overall vote in that state.

Another great thing you can use a heat map for is to map what visitors to your site click on. The more a particular section is clicked the ‘hotter’ the colour will turn, from blue to bright yellow to red.

#10 - Scatter plot

If you present your data in dots instead of chunky bars, you’ll have a scatter plot. 

A scatter plot is a grid with several inputs showing the relationship between two variables. It’s good at collecting seemingly random data and revealing some telling trends.

For example, in this graph, each dot shows the average daily temperature versus the number of beach visitors across several days. You can see that the dots get higher as the temperature increases, so it’s likely that hotter weather leads to more visitors.

5 Data Presentation Mistakes to Avoid

#1 - assume your audience understands what the numbers represent.

You may know all the behind-the-scenes of your data since you’ve worked with them for weeks, but your audience doesn’t.

Showing without telling only invites more and more questions from your audience, as they have to constantly make sense of your data, wasting the time of both sides as a result.

While showing your data presentations, you should tell them what the data are about before hitting them with waves of numbers first. You can use interactive activities such as polls , word clouds , online quizzes and Q&A sections , combined with icebreaker games , to assess their understanding of the data and address any confusion beforehand.

#2 - Use the wrong type of chart

Charts such as pie charts must have a total of 100% so if your numbers accumulate to 193% like this example below, you’re definitely doing it wrong.

Before making a chart, ask yourself: what do I want to accomplish with my data? Do you want to see the relationship between the data sets, show the up and down trends of your data, or see how segments of one thing make up a whole?

Remember, clarity always comes first. Some data visualisations may look cool, but if they don’t fit your data, steer clear of them. 

#3 - Make it 3D

3D is a fascinating graphical presentation example. The third dimension is cool, but full of risks.

Can you see what’s behind those red bars? Because we can’t either. You may think that 3D charts add more depth to the design, but they can create false perceptions as our eyes see 3D objects closer and bigger than they appear, not to mention they cannot be seen from multiple angles.

#4 - Use different types of charts to compare contents in the same category

This is like comparing a fish to a monkey. Your audience won’t be able to identify the differences and make an appropriate correlation between the two data sets. 

Next time, stick to one type of data presentation only. Avoid the temptation of trying various data visualisation methods in one go and make your data as accessible as possible.

#5 - Bombard the audience with too much information

The goal of data presentation is to make complex topics much easier to understand, and if you’re bringing too much information to the table, you’re missing the point.

The more information you give, the more time it will take for your audience to process it all. If you want to make your data understandable and give your audience a chance to remember it, keep the information within it to an absolute minimum. You should end your session with open-ended questions to see what your participants really think.

What are the Best Methods of Data Presentation?

Finally, which is the best way to present data?

The answer is…

There is none! Each type of presentation has its own strengths and weaknesses and the one you choose greatly depends on what you’re trying to do. 

For example:

• Go for a scatter plot if you’re exploring the relationship between different data values, like seeing whether the sales of ice cream go up because of the temperature or because people are just getting more hungry and greedy each day?
• Go for a line graph if you want to mark a trend over time. 
• Go for a heat map if you like some fancy visualisation of the changes in a geographical location, or to see your visitors' behaviour on your website.
• Go for a pie chart (especially in 3D) if you want to be shunned by others because it was never a good idea👇

Frequently Asked Questions

What is a chart presentation.

A chart presentation is a way of presenting data or information using visual aids such as charts, graphs, and diagrams. The purpose of a chart presentation is to make complex information more accessible and understandable for the audience.

When can I use charts for the presentation?

Charts can be used to compare data, show trends over time, highlight patterns, and simplify complex information.

Why should you use charts for presentation?

You should use charts to ensure your contents and visuals look clean, as they are the visual representative, provide clarity, simplicity, comparison, contrast and super time-saving!

What are the 4 graphical methods of presenting data?

Histogram, Smoothed frequency graph, Pie diagram or Pie chart, Cumulative or ogive frequency graph, and Frequency Polygon.

Leah Nguyen

Words that convert, stories that stick. I turn complex ideas into engaging narratives - helping audiences learn, remember, and take action.

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It is the simplest form of data Presentation often used in schools or universities to provide a clearer picture to students, who are better able to capture the concepts effectively through a pictorial Presentation of simple data.

2. Column chart

It is a simplified version of the pictorial Presentation which involves the management of a larger amount of data being shared during the presentations and providing suitable clarity to the insights of the data.

3. Pie Charts

Pie charts provide a very descriptive & a 2D depiction of the data pertaining to comparisons or resemblance of data in two separate fields.

4. Bar charts

A bar chart that shows the accumulation of data with cuboid bars with different dimensions & lengths which are directly proportionate to the values they represent. The bars can be placed either vertically or horizontally depending on the data being represented.

5. Histograms

It is a perfect Presentation of the spread of numerical data. The main differentiation that separates data graphs and histograms are the gaps in the data graphs.

6. Box plots

Box plot or Box-plot is a way of representing groups of numerical data through quartiles. Data Presentation is easier with this style of graph dealing with the extraction of data to the minutes of difference.

Map Data graphs help you with data Presentation over an area to display the areas of concern. Map graphs are useful to make an exact depiction of data over a vast case scenario.

All these visual presentations share a common goal of creating meaningful insights and a platform to understand and manage the data in relation to the growth and expansion of one’s in-depth understanding of data & details to plan or execute future decisions or actions.

Importance of Data Presentation

Data Presentation could be both can be a deal maker or deal breaker based on the delivery of the content in the context of visual depiction.

Data Presentation tools are powerful communication tools that can simplify the data by making it easily understandable & readable at the same time while attracting & keeping the interest of its readers and effectively showcase large amounts of complex data in a simplified manner.

If the user can create an insightful presentation of the data in hand with the same sets of facts and figures, then the results promise to be impressive.

There have been situations where the user has had a great amount of data and vision for expansion but the presentation drowned his/her vision.

To impress the higher management and top brass of a firm, effective presentation of data is needed.

Data Presentation helps the clients or the audience to not spend time grasping the concept and the future alternatives of the business and to convince them to invest in the company & turn it profitable both for the investors & the company.

Although data presentation has a lot to offer, the following are some of the major reason behind the essence of an effective presentation:-

• Many consumers or higher authorities are interested in the interpretation of data, not the raw data itself. Therefore, after the analysis of the data, users should represent the data with a visual aspect for better understanding and knowledge.
• The user should not overwhelm the audience with a number of slides of the presentation and inject an ample amount of texts as pictures that will speak for themselves.
• Data presentation often happens in a nutshell with each department showcasing their achievements towards company growth through a graph or a histogram.
• Providing a brief description would help the user to attain attention in a small amount of time while informing the audience about the context of the presentation
• The inclusion of pictures, charts, graphs and tables in the presentation help for better understanding the potential outcomes.
• An effective presentation would allow the organization to determine the difference with the fellow organization and acknowledge its flaws. Comparison of data would assist them in decision making.

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Home Blog Design Understanding Data Presentations (Guide + Examples)

Understanding Data Presentations (Guide + Examples)

In this age of overwhelming information, the skill to effectively convey data has become extremely valuable. Initiating a discussion on data presentation types involves thoughtful consideration of the nature of your data and the message you aim to convey. Different types of visualizations serve distinct purposes. Whether you’re dealing with how to develop a report or simply trying to communicate complex information, how you present data influences how well your audience understands and engages with it. This extensive guide leads you through the different ways of data presentation.

Table of Contents

What is a Data Presentation?

What should a data presentation include, line graphs, treemap chart, scatter plot, how to choose a data presentation type, recommended data presentation templates, common mistakes done in data presentation.

A data presentation is a slide deck that aims to disclose quantitative information to an audience through the use of visual formats and narrative techniques derived from data analysis, making complex data understandable and actionable. This process requires a series of tools, such as charts, graphs, tables, infographics, dashboards, and so on, supported by concise textual explanations to improve understanding and boost retention rate.

Data presentations require us to cull data in a format that allows the presenter to highlight trends, patterns, and insights so that the audience can act upon the shared information. In a few words, the goal of data presentations is to enable viewers to grasp complicated concepts or trends quickly, facilitating informed decision-making or deeper analysis.

Data presentations go beyond the mere usage of graphical elements. Seasoned presenters encompass visuals with the art of data storytelling , so the speech skillfully connects the points through a narrative that resonates with the audience. Depending on the purpose – inspire, persuade, inform, support decision-making processes, etc. – is the data presentation format that is better suited to help us in this journey.

To nail your upcoming data presentation, ensure to count with the following elements:

• Clear Objectives: Understand the intent of your presentation before selecting the graphical layout and metaphors to make content easier to grasp.
• Engaging introduction: Use a powerful hook from the get-go. For instance, you can ask a big question or present a problem that your data will answer. Take a look at our guide on how to start a presentation for tips & insights.
• Structured Narrative: Your data presentation must tell a coherent story. This means a beginning where you present the context, a middle section in which you present the data, and an ending that uses a call-to-action. Check our guide on presentation structure for further information.
• Visual Elements: These are the charts, graphs, and other elements of visual communication we ought to use to present data. This article will cover one by one the different types of data representation methods we can use, and provide further guidance on choosing between them.
• Insights and Analysis: This is not just showcasing a graph and letting people get an idea about it. A proper data presentation includes the interpretation of that data, the reason why it’s included, and why it matters to your research.
• Conclusion & CTA: Ending your presentation with a call to action is necessary. Whether you intend to wow your audience into acquiring your services, inspire them to change the world, or whatever the purpose of your presentation, there must be a stage in which you convey all that you shared and show the path to staying in touch. Plan ahead whether you want to use a thank-you slide, a video presentation, or which method is apt and tailored to the kind of presentation you deliver.
• Q&A Session: After your speech is concluded, allocate 3-5 minutes for the audience to raise any questions about the information you disclosed. This is an extra chance to establish your authority on the topic. Check our guide on questions and answer sessions in presentations here.

Bar charts are a graphical representation of data using rectangular bars to show quantities or frequencies in an established category. They make it easy for readers to spot patterns or trends. Bar charts can be horizontal or vertical, although the vertical format is commonly known as a column chart. They display categorical, discrete, or continuous variables grouped in class intervals [1] . They include an axis and a set of labeled bars horizontally or vertically. These bars represent the frequencies of variable values or the values themselves. Numbers on the y-axis of a vertical bar chart or the x-axis of a horizontal bar chart are called the scale.

Real-Life Application of Bar Charts

Let’s say a sales manager is presenting sales to their audience. Using a bar chart, he follows these steps.

Step 1: Selecting Data

The first step is to identify the specific data you will present to your audience.

The sales manager has highlighted these products for the presentation.

• Product A: Men’s Shoes
• Product B: Women’s Apparel
• Product C: Electronics
• Product D: Home Decor

Step 2: Choosing Orientation

Opt for a vertical layout for simplicity. Vertical bar charts help compare different categories in case there are not too many categories [1] . They can also help show different trends. A vertical bar chart is used where each bar represents one of the four chosen products. After plotting the data, it is seen that the height of each bar directly represents the sales performance of the respective product.

It is visible that the tallest bar (Electronics – Product C) is showing the highest sales. However, the shorter bars (Women’s Apparel – Product B and Home Decor – Product D) need attention. It indicates areas that require further analysis or strategies for improvement.

Step 3: Colorful Insights

Different colors are used to differentiate each product. It is essential to show a color-coded chart where the audience can distinguish between products.

• Men’s Shoes (Product A): Yellow
• Women’s Apparel (Product B): Orange
• Electronics (Product C): Violet
• Home Decor (Product D): Blue

Bar charts are straightforward and easily understandable for presenting data. They are versatile when comparing products or any categorical data [2] . Bar charts adapt seamlessly to retail scenarios. Despite that, bar charts have a few shortcomings. They cannot illustrate data trends over time. Besides, overloading the chart with numerous products can lead to visual clutter, diminishing its effectiveness.

For more information, check our collection of bar chart templates for PowerPoint .

Line graphs help illustrate data trends, progressions, or fluctuations by connecting a series of data points called ‘markers’ with straight line segments. This provides a straightforward representation of how values change [5] . Their versatility makes them invaluable for scenarios requiring a visual understanding of continuous data. In addition, line graphs are also useful for comparing multiple datasets over the same timeline. Using multiple line graphs allows us to compare more than one data set. They simplify complex information so the audience can quickly grasp the ups and downs of values. From tracking stock prices to analyzing experimental results, you can use line graphs to show how data changes over a continuous timeline. They show trends with simplicity and clarity.

Real-life Application of Line Graphs

To understand line graphs thoroughly, we will use a real case. Imagine you’re a financial analyst presenting a tech company’s monthly sales for a licensed product over the past year. Investors want insights into sales behavior by month, how market trends may have influenced sales performance and reception to the new pricing strategy. To present data via a line graph, you will complete these steps.

First, you need to gather the data. In this case, your data will be the sales numbers. For example:

• January: $45,000
• February: $55,000
• March: $45,000
• April: $60,000
• May: $ 70,000
• June: $65,000
• July: $62,000
• August: $68,000
• September: $81,000
• October: $76,000
• November: $87,000
• December: $91,000

After choosing the data, the next step is to select the orientation. Like bar charts, you can use vertical or horizontal line graphs. However, we want to keep this simple, so we will keep the timeline (x-axis) horizontal while the sales numbers (y-axis) vertical.

Step 3: Connecting Trends

After adding the data to your preferred software, you will plot a line graph. In the graph, each month’s sales are represented by data points connected by a line.

Step 4: Adding Clarity with Color

If there are multiple lines, you can also add colors to highlight each one, making it easier to follow.

Line graphs excel at visually presenting trends over time. These presentation aids identify patterns, like upward or downward trends. However, too many data points can clutter the graph, making it harder to interpret. Line graphs work best with continuous data but are not suitable for categories.

For more information, check our collection of line chart templates for PowerPoint and our article about how to make a presentation graph .

A data dashboard is a visual tool for analyzing information. Different graphs, charts, and tables are consolidated in a layout to showcase the information required to achieve one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs). You don’t make new visuals in the dashboard; instead, you use it to display visuals you’ve already made in worksheets [3] .

Keeping the number of visuals on a dashboard to three or four is recommended. Adding too many can make it hard to see the main points [4]. Dashboards can be used for business analytics to analyze sales, revenue, and marketing metrics at a time. They are also used in the manufacturing industry, as they allow users to grasp the entire production scenario at the moment while tracking the core KPIs for each line.

Real-Life Application of a Dashboard

Consider a project manager presenting a software development project’s progress to a tech company’s leadership team. He follows the following steps.

Step 1: Defining Key Metrics

To effectively communicate the project’s status, identify key metrics such as completion status, budget, and bug resolution rates. Then, choose measurable metrics aligned with project objectives.

Step 2: Choosing Visualization Widgets

After finalizing the data, presentation aids that align with each metric are selected. For this project, the project manager chooses a progress bar for the completion status and uses bar charts for budget allocation. Likewise, he implements line charts for bug resolution rates.

Step 3: Dashboard Layout

Key metrics are prominently placed in the dashboard for easy visibility, and the manager ensures that it appears clean and organized.

Dashboards provide a comprehensive view of key project metrics. Users can interact with data, customize views, and drill down for detailed analysis. However, creating an effective dashboard requires careful planning to avoid clutter. Besides, dashboards rely on the availability and accuracy of underlying data sources.

For more information, check our article on how to design a dashboard presentation , and discover our collection of dashboard PowerPoint templates .

Treemap charts represent hierarchical data structured in a series of nested rectangles [6] . As each branch of the ‘tree’ is given a rectangle, smaller tiles can be seen representing sub-branches, meaning elements on a lower hierarchical level than the parent rectangle. Each one of those rectangular nodes is built by representing an area proportional to the specified data dimension.

Treemaps are useful for visualizing large datasets in compact space. It is easy to identify patterns, such as which categories are dominant. Common applications of the treemap chart are seen in the IT industry, such as resource allocation, disk space management, website analytics, etc. Also, they can be used in multiple industries like healthcare data analysis, market share across different product categories, or even in finance to visualize portfolios.

Real-Life Application of a Treemap Chart

Let’s consider a financial scenario where a financial team wants to represent the budget allocation of a company. There is a hierarchy in the process, so it is helpful to use a treemap chart. In the chart, the top-level rectangle could represent the total budget, and it would be subdivided into smaller rectangles, each denoting a specific department. Further subdivisions within these smaller rectangles might represent individual projects or cost categories.

Step 1: Define Your Data Hierarchy

While presenting data on the budget allocation, start by outlining the hierarchical structure. The sequence will be like the overall budget at the top, followed by departments, projects within each department, and finally, individual cost categories for each project.

• Top-level rectangle: Total Budget
• Second-level rectangles: Departments (Engineering, Marketing, Sales)
• Third-level rectangles: Projects within each department
• Fourth-level rectangles: Cost categories for each project (Personnel, Marketing Expenses, Equipment)

Step 2: Choose a Suitable Tool

It’s time to select a data visualization tool supporting Treemaps. Popular choices include Tableau, Microsoft Power BI, PowerPoint, or even coding with libraries like D3.js. It is vital to ensure that the chosen tool provides customization options for colors, labels, and hierarchical structures.

Here, the team uses PowerPoint for this guide because of its user-friendly interface and robust Treemap capabilities.

Step 3: Make a Treemap Chart with PowerPoint

After opening the PowerPoint presentation, they chose “SmartArt” to form the chart. The SmartArt Graphic window has a “Hierarchy” category on the left.  Here, you will see multiple options. You can choose any layout that resembles a Treemap. The “Table Hierarchy” or “Organization Chart” options can be adapted. The team selects the Table Hierarchy as it looks close to a Treemap.

Step 5: Input Your Data

After that, a new window will open with a basic structure. They add the data one by one by clicking on the text boxes. They start with the top-level rectangle, representing the total budget.  

Step 6: Customize the Treemap

By clicking on each shape, they customize its color, size, and label. At the same time, they can adjust the font size, style, and color of labels by using the options in the “Format” tab in PowerPoint. Using different colors for each level enhances the visual difference.

Treemaps excel at illustrating hierarchical structures. These charts make it easy to understand relationships and dependencies. They efficiently use space, compactly displaying a large amount of data, reducing the need for excessive scrolling or navigation. Additionally, using colors enhances the understanding of data by representing different variables or categories.

In some cases, treemaps might become complex, especially with deep hierarchies.  It becomes challenging for some users to interpret the chart. At the same time, displaying detailed information within each rectangle might be constrained by space. It potentially limits the amount of data that can be shown clearly. Without proper labeling and color coding, there’s a risk of misinterpretation.

A heatmap is a data visualization tool that uses color coding to represent values across a two-dimensional surface. In these, colors replace numbers to indicate the magnitude of each cell. This color-shaded matrix display is valuable for summarizing and understanding data sets with a glance [7] . The intensity of the color corresponds to the value it represents, making it easy to identify patterns, trends, and variations in the data.

As a tool, heatmaps help businesses analyze website interactions, revealing user behavior patterns and preferences to enhance overall user experience. In addition, companies use heatmaps to assess content engagement, identifying popular sections and areas of improvement for more effective communication. They excel at highlighting patterns and trends in large datasets, making it easy to identify areas of interest.

We can implement heatmaps to express multiple data types, such as numerical values, percentages, or even categorical data. Heatmaps help us easily spot areas with lots of activity, making them helpful in figuring out clusters [8] . When making these maps, it is important to pick colors carefully. The colors need to show the differences between groups or levels of something. And it is good to use colors that people with colorblindness can easily see.

Check our detailed guide on how to create a heatmap here. Also discover our collection of heatmap PowerPoint templates .

Pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice represents a proportionate part of the whole, making it easy to visualize the contribution of each component to the total.

The size of the pie charts is influenced by the value of data points within each pie. The total of all data points in a pie determines its size. The pie with the highest data points appears as the largest, whereas the others are proportionally smaller. However, you can present all pies of the same size if proportional representation is not required [9] . Sometimes, pie charts are difficult to read, or additional information is required. A variation of this tool can be used instead, known as the donut chart , which has the same structure but a blank center, creating a ring shape. Presenters can add extra information, and the ring shape helps to declutter the graph.

Pie charts are used in business to show percentage distribution, compare relative sizes of categories, or present straightforward data sets where visualizing ratios is essential.

Real-Life Application of Pie Charts

Consider a scenario where you want to represent the distribution of the data. Each slice of the pie chart would represent a different category, and the size of each slice would indicate the percentage of the total portion allocated to that category.

Step 1: Define Your Data Structure

Imagine you are presenting the distribution of a project budget among different expense categories.

• Column A: Expense Categories (Personnel, Equipment, Marketing, Miscellaneous)
• Column B: Budget Amounts ($40,000, $30,000, $20,000, $10,000) Column B represents the values of your categories in Column A.

Step 2: Insert a Pie Chart

Using any of the accessible tools, you can create a pie chart. The most convenient tools for forming a pie chart in a presentation are presentation tools such as PowerPoint or Google Slides.  You will notice that the pie chart assigns each expense category a percentage of the total budget by dividing it by the total budget.

For instance:

• Personnel: $40,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 40%
• Equipment: $30,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 30%
• Marketing: $20,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 20%
• Miscellaneous: $10,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 10%

You can make a chart out of this or just pull out the pie chart from the data.

3D pie charts and 3D donut charts are quite popular among the audience. They stand out as visual elements in any presentation slide, so let’s take a look at how our pie chart example would look in 3D pie chart format.

Step 03: Results Interpretation

The pie chart visually illustrates the distribution of the project budget among different expense categories. Personnel constitutes the largest portion at 40%, followed by equipment at 30%, marketing at 20%, and miscellaneous at 10%. This breakdown provides a clear overview of where the project funds are allocated, which helps in informed decision-making and resource management. It is evident that personnel are a significant investment, emphasizing their importance in the overall project budget.

Pie charts provide a straightforward way to represent proportions and percentages. They are easy to understand, even for individuals with limited data analysis experience. These charts work well for small datasets with a limited number of categories.

However, a pie chart can become cluttered and less effective in situations with many categories. Accurate interpretation may be challenging, especially when dealing with slight differences in slice sizes. In addition, these charts are static and do not effectively convey trends over time.

For more information, check our collection of pie chart templates for PowerPoint .

Histograms present the distribution of numerical variables. Unlike a bar chart that records each unique response separately, histograms organize numeric responses into bins and show the frequency of reactions within each bin [10] . The x-axis of a histogram shows the range of values for a numeric variable. At the same time, the y-axis indicates the relative frequencies (percentage of the total counts) for that range of values.

Whenever you want to understand the distribution of your data, check which values are more common, or identify outliers, histograms are your go-to. Think of them as a spotlight on the story your data is telling. A histogram can provide a quick and insightful overview if you’re curious about exam scores, sales figures, or any numerical data distribution.

Real-Life Application of a Histogram

In the histogram data analysis presentation example, imagine an instructor analyzing a class’s grades to identify the most common score range. A histogram could effectively display the distribution. It will show whether most students scored in the average range or if there are significant outliers.

Step 1: Gather Data

He begins by gathering the data. The scores of each student in class are gathered to analyze exam scores.

After arranging the scores in ascending order, bin ranges are set.

Step 2: Define Bins

Bins are like categories that group similar values. Think of them as buckets that organize your data. The presenter decides how wide each bin should be based on the range of the values. For instance, the instructor sets the bin ranges based on score intervals: 60-69, 70-79, 80-89, and 90-100.

Step 3: Count Frequency

Now, he counts how many data points fall into each bin. This step is crucial because it tells you how often specific ranges of values occur. The result is the frequency distribution, showing the occurrences of each group.

Here, the instructor counts the number of students in each category.

• 60-69: 1 student (Kate)
• 70-79: 4 students (David, Emma, Grace, Jack)
• 80-89: 7 students (Alice, Bob, Frank, Isabel, Liam, Mia, Noah)
• 90-100: 3 students (Clara, Henry, Olivia)

Step 4: Create the Histogram

It’s time to turn the data into a visual representation. Draw a bar for each bin on a graph. The width of the bar should correspond to the range of the bin, and the height should correspond to the frequency.  To make your histogram understandable, label the X and Y axes.

In this case, the X-axis should represent the bins (e.g., test score ranges), and the Y-axis represents the frequency.

The histogram of the class grades reveals insightful patterns in the distribution. Most students, with seven students, fall within the 80-89 score range. The histogram provides a clear visualization of the class’s performance. It showcases a concentration of grades in the upper-middle range with few outliers at both ends. This analysis helps in understanding the overall academic standing of the class. It also identifies the areas for potential improvement or recognition.

Thus, histograms provide a clear visual representation of data distribution. They are easy to interpret, even for those without a statistical background. They apply to various types of data, including continuous and discrete variables. One weak point is that histograms do not capture detailed patterns in students’ data, with seven compared to other visualization methods.

A scatter plot is a graphical representation of the relationship between two variables. It consists of individual data points on a two-dimensional plane. This plane plots one variable on the x-axis and the other on the y-axis. Each point represents a unique observation. It visualizes patterns, trends, or correlations between the two variables.

Scatter plots are also effective in revealing the strength and direction of relationships. They identify outliers and assess the overall distribution of data points. The points’ dispersion and clustering reflect the relationship’s nature, whether it is positive, negative, or lacks a discernible pattern. In business, scatter plots assess relationships between variables such as marketing cost and sales revenue. They help present data correlations and decision-making.

Real-Life Application of Scatter Plot

A group of scientists is conducting a study on the relationship between daily hours of screen time and sleep quality. After reviewing the data, they managed to create this table to help them build a scatter plot graph:

In the provided example, the x-axis represents Daily Hours of Screen Time, and the y-axis represents the Sleep Quality Rating.

The scientists observe a negative correlation between the amount of screen time and the quality of sleep. This is consistent with their hypothesis that blue light, especially before bedtime, has a significant impact on sleep quality and metabolic processes.

There are a few things to remember when using a scatter plot. Even when a scatter diagram indicates a relationship, it doesn’t mean one variable affects the other. A third factor can influence both variables. The more the plot resembles a straight line, the stronger the relationship is perceived [11] . If it suggests no ties, the observed pattern might be due to random fluctuations in data. When the scatter diagram depicts no correlation, whether the data might be stratified is worth considering.

Choosing the appropriate data presentation type is crucial when making a presentation . Understanding the nature of your data and the message you intend to convey will guide this selection process. For instance, when showcasing quantitative relationships, scatter plots become instrumental in revealing correlations between variables. If the focus is on emphasizing parts of a whole, pie charts offer a concise display of proportions. Histograms, on the other hand, prove valuable for illustrating distributions and frequency patterns. 

Bar charts provide a clear visual comparison of different categories. Likewise, line charts excel in showcasing trends over time, while tables are ideal for detailed data examination. Starting a presentation on data presentation types involves evaluating the specific information you want to communicate and selecting the format that aligns with your message. This ensures clarity and resonance with your audience from the beginning of your presentation.

1. Fact Sheet Dashboard for Data Presentation

Convey all the data you need to present in this one-pager format, an ideal solution tailored for users looking for presentation aids. Global maps, donut chats, column graphs, and text neatly arranged in a clean layout presented in light and dark themes.

Use This Template

2. 3D Column Chart Infographic PPT Template

Represent column charts in a highly visual 3D format with this PPT template. A creative way to present data, this template is entirely editable, and we can craft either a one-page infographic or a series of slides explaining what we intend to disclose point by point.

3. Data Circles Infographic PowerPoint Template

An alternative to the pie chart and donut chart diagrams, this template features a series of curved shapes with bubble callouts as ways of presenting data. Expand the information for each arch in the text placeholder areas.

4. Colorful Metrics Dashboard for Data Presentation

This versatile dashboard template helps us in the presentation of the data by offering several graphs and methods to convert numbers into graphics. Implement it for e-commerce projects, financial projections, project development, and more.

5. Animated Data Presentation Tools for PowerPoint & Google Slides

A slide deck filled with most of the tools mentioned in this article, from bar charts, column charts, treemap graphs, pie charts, histogram, etc. Animated effects make each slide look dynamic when sharing data with stakeholders.

6. Statistics Waffle Charts PPT Template for Data Presentations

This PPT template helps us how to present data beyond the typical pie chart representation. It is widely used for demographics, so it’s a great fit for marketing teams, data science professionals, HR personnel, and more.

7. Data Presentation Dashboard Template for Google Slides

A compendium of tools in dashboard format featuring line graphs, bar charts, column charts, and neatly arranged placeholder text areas. 

8. Weather Dashboard for Data Presentation

Share weather data for agricultural presentation topics, environmental studies, or any kind of presentation that requires a highly visual layout for weather forecasting on a single day. Two color themes are available.

9. Social Media Marketing Dashboard Data Presentation Template

Intended for marketing professionals, this dashboard template for data presentation is a tool for presenting data analytics from social media channels. Two slide layouts featuring line graphs and column charts.

10. Project Management Summary Dashboard Template

A tool crafted for project managers to deliver highly visual reports on a project’s completion, the profits it delivered for the company, and expenses/time required to execute it. 4 different color layouts are available.

11. Profit & Loss Dashboard for PowerPoint and Google Slides

A must-have for finance professionals. This typical profit & loss dashboard includes progress bars, donut charts, column charts, line graphs, and everything that’s required to deliver a comprehensive report about a company’s financial situation.

Overwhelming visuals

One of the mistakes related to using data-presenting methods is including too much data or using overly complex visualizations. They can confuse the audience and dilute the key message.

Inappropriate chart types

Choosing the wrong type of chart for the data at hand can lead to misinterpretation. For example, using a pie chart for data that doesn’t represent parts of a whole is not right.

Lack of context

Failing to provide context or sufficient labeling can make it challenging for the audience to understand the significance of the presented data.

Inconsistency in design

Using inconsistent design elements and color schemes across different visualizations can create confusion and visual disarray.

Failure to provide details

Simply presenting raw data without offering clear insights or takeaways can leave the audience without a meaningful conclusion.

Lack of focus

Not having a clear focus on the key message or main takeaway can result in a presentation that lacks a central theme.

Visual accessibility issues

Overlooking the visual accessibility of charts and graphs can exclude certain audience members who may have difficulty interpreting visual information.

In order to avoid these mistakes in data presentation, presenters can benefit from using presentation templates . These templates provide a structured framework. They ensure consistency, clarity, and an aesthetically pleasing design, enhancing data communication’s overall impact.

Understanding and choosing data presentation types are pivotal in effective communication. Each method serves a unique purpose, so selecting the appropriate one depends on the nature of the data and the message to be conveyed. The diverse array of presentation types offers versatility in visually representing information, from bar charts showing values to pie charts illustrating proportions. 

Using the proper method enhances clarity, engages the audience, and ensures that data sets are not just presented but comprehensively understood. By appreciating the strengths and limitations of different presentation types, communicators can tailor their approach to convey information accurately, developing a deeper connection between data and audience understanding.

[1] Government of Canada, S.C. (2021) 5 Data Visualization 5.2 Bar Chart , 5.2 Bar chart .  https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch9/bargraph-diagrammeabarres/5214818-eng.htm

[2] Kosslyn, S.M., 1989. Understanding charts and graphs. Applied cognitive psychology, 3(3), pp.185-225. https://apps.dtic.mil/sti/pdfs/ADA183409.pdf

[3] Creating a Dashboard . https://it.tufts.edu/book/export/html/1870

[4] https://www.goldenwestcollege.edu/research/data-and-more/data-dashboards/index.html

[5] https://www.mit.edu/course/21/21.guide/grf-line.htm

[6] Jadeja, M. and Shah, K., 2015, January. Tree-Map: A Visualization Tool for Large Data. In GSB@ SIGIR (pp. 9-13). https://ceur-ws.org/Vol-1393/gsb15proceedings.pdf#page=15

[7] Heat Maps and Quilt Plots. https://www.publichealth.columbia.edu/research/population-health-methods/heat-maps-and-quilt-plots

[8] EIU QGIS WORKSHOP. https://www.eiu.edu/qgisworkshop/heatmaps.php

[9] About Pie Charts.  https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c8.htm

[10] Histograms. https://sites.utexas.edu/sos/guided/descriptive/numericaldd/descriptiven2/histogram/ [11] https://asq.org/quality-resources/scatter-diagram

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10 Superb Data Presentation Examples To Learn From

The best way to learn how to present data effectively is to see data presentation examples from the professionals in the field.

We collected superb examples of graphical presentation and visualization of data in statistics, research, sales, marketing, business management, and other areas.

On this page:

How to present data effectively? Clever tips.

• 10 Real-life examples of data presentation with interpretation.

Download the above infographic in PDF

Your audience should be able to walk through the graphs and visualizations easily while enjoy and respond to the story.

[bctt tweet=”Your reports and graphical presentations should not just deliver statistics, numbers, and data. Instead, they must tell a story, illustrate a situation, provide proofs, win arguments, and even change minds.” username=””]

Before going to data presentation examples let’s see some essential tips to help you build powerful data presentations.

1. Keep it simple and clear

The presentation should be focused on your key message and you need to illustrate it very briefly.

Graphs and charts should communicate your core message, not distract from it. A complicated and overloaded chart can distract and confuse. Eliminate anything repetitive or decorative.

2. Pick up the right visuals for the job

A vast number of types of graphs and charts are available at your disposal – pie charts, line and bar graphs, scatter plot , Venn diagram , etc.

Choosing the right type of chart can be a tricky business. Practically, the choice depends on 2 major things: on the kind of analysis you want to present and on the data types you have.

Commonly, when we aim to facilitate a comparison, we use a bar chart or radar chart. When we want to show trends over time, we use a line chart or an area chart and etc.

3. Break the complex concepts into multiple graphics

It’s can be very hard for a public to understand a complicated graphical visualization. Don’t present it as a huge amount of visual data.

Instead, break the graphics into pieces and illustrate how each piece corresponds to the previous one.

4. Carefully choose the colors

Colors provoke different emotions and associations that affect the way your brand or story is perceived. Sometimes color choices can make or break your visuals.

It is no need to be a designer to make the right color selections. Some golden rules are to stick to 3 or 4 colors avoiding full-on rainbow look and to borrow ideas from relevant chart designs.

Another tip is to consider the brand attributes and your audience profile. You will see appropriate color use in the below data presentation examples.

5. Don’t leave a lot of room for words

The key point in graphical data presentation is to tell the story using visuals and images, not words. Give your audience visual facts, not text.

However, that doesn’t mean words have no importance.

A great advice here is to think that every letter is critical, and there’s no room for wasted and empty words. Also, don’t create generic titles and headlines, build them around the core message.

6. Use good templates and software tools

Building data presentation with AI nowadays means using some kind of software programs and templates. There are many available options – from free graphing software solutions to advanced data visualization tools.

Choosing a good software gives you the power to create good and high-quality visualizations. Make sure you are using templates that provides characteristics like colors, fonts, and chart styles.

A small investment of time to research the software options prevents a large loss of productivity and efficiency at the end.

10 Superb data presentation examples 

Here we collected some of the best examples of data presentation made by one of the biggest names in the graphical data visualization software and information research.

These brands put a lot of money and efforts to investigate how professional graphs and charts should look.

1. Sales Stage History  Funnel Chart 

Data is beautiful and this sales stage funnel chart by Zoho Reports prove this. The above funnel chart represents the different stages in a sales process (Qualification, Need Analysis, Initial Offer, etc.) and shows the potential revenue for each stage for the last and this quarter.

The potential revenue for each sales stage is displayed by a different color and sized according to the amount. The chart is very colorful, eye-catching, and intriguing.

2. Facebook Ads Data Presentation Examples

These are other data presentation examples from Zoho Reports. The first one is a stacked bar chart that displays the impressions breakdown by months and types of Facebook campaigns.

Impressions are one of the vital KPI examples in digital marketing intelligence and business. The first graph is designed to help you compare and notice sharp differences at the Facebook campaigns that have the most influence on impression movements.

The second one is an area chart that shows the changes in the costs for the same Facebook campaigns over the months.

The 2 examples illustrate how multiple and complicated data can be presented clearly and simply in a visually appealing way.

3. Sales Opportunity Data Presentation

These two bar charts (stacked and horizontal bar charts) by Microsoft Power Bi are created to track sales opportunities and revenue by region and sales stage.

The stacked bar graph shows the revenue probability in percentage determined by the current sales stage (Lead, Quality, Solution…) over the months. The horizontal bar chart represents the size of the sales opportunity (Small, Medium, Large) according to regions (East, Central, West).

Both graphs are impressive ways for a sales manager to introduce the upcoming opportunity to C-level managers and stakeholders. The color combination is rich but easy to digest.

4. Power 100 Data Visualization 

Want to show hierarchical data? Treemaps can be perfect for the job. This is a stunning treemap example by Infogram.com that shows you who are the most influential industries. As you see the Government is on the top.

This treemap is a very compact and space-efficient visualization option for presenting hierarchies, that gives you a quick overview of the structure of the most powerful industries.

So beautiful way to compare the proportions between things via their area size.

When it comes to best research data presentation examples in statistics, Nielsen information company is an undoubted leader. The above professional looking line graph by Nielsen represent the slowing alcoholic grow of 4 alcohol categories (Beer, Wine, Spirits, CPG) for the period of 12 months.

The chart is an ideal example of a data visualization that incorporates all the necessary elements of an effective and engaging graph. It uses color to let you easily differentiate trends and allows you to get a global sense of the data. Additionally, it is incredibly simple to understand.

6. Digital Health Research Data Visualization Example

Digital health is a very hot topic nowadays and this stunning donut chart by IQVIA shows the proportion of different mobile health apps by therapy area (Mental Health, Diabetes, Kidney Disease, and etc.). 100% = 1749 unique apps.

This is a wonderful example of research data presentation that provides evidence of Digital Health’s accelerating innovation and app expansion.

Besides good-looking, this donut chart is very space-efficient because the blank space inside it is used to display information too.

7. Disease Research Data Visualization Examples

Presenting relationships among different variables is hard to understand and confusing -especially when there is a huge number of them. But using the appropriate visuals and colors, the IQVIA did a great job simplifying this data into a clear and digestible format.

The above stacked bar charts by IQVIA represents the distribution of oncology medicine spendings by years and product segments (Protected Brand Price, Protected Brand Volume, New Brands, etc.).

The chart allows you to clearly see the changes in spendings and where they occurred – a great example of telling a deeper story in a simple way.

8. Textual and Qualitative Data Presentation Example

When it comes to easy to understand and good looking textual and qualitative data visualization, pyramid graph has a top place. To know what is qualitative data see our post quantitative vs qualitative data .

9. Product Metrics Graph Example

If you are searching for excel data presentation examples, this stylish template from Smartsheet can give you good ideas for professional looking design.

The above stacked bar chart represents product revenue breakdown by months and product items. It reveals patterns and trends over the first half of the year that can be a good basis for data-driven decision-making .

10. Supply Chain Data Visualization Example 

This bar chart created by ClicData  is an excellent example of how trends over time can be effectively and professionally communicated through the use of well-presented visualization.

It shows the dynamics of pricing through the months based on units sold, units shipped, and current inventory. This type of graph pack a whole lot of information into a simple visual. In addition, the chart is connected to real data and is fully interactive.

The above data presentation examples aim to help you learn how to present data effectively and professionally.

About The Author

Silvia Valcheva

Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc.

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Blog Data Visualization 10 Data Presentation Examples For Strategic Communication

10 Data Presentation Examples For Strategic Communication

Written by: Krystle Wong Sep 28, 2023

Knowing how to present data is like having a superpower. 

Data presentation today is no longer just about numbers on a screen; it’s storytelling with a purpose. It’s about captivating your audience, making complex stuff look simple and inspiring action. 

To help turn your data into stories that stick, influence decisions and make an impact, check out Venngage’s free chart maker or follow me on a tour into the world of data storytelling along with data presentation templates that work across different fields, from business boardrooms to the classroom and beyond. Keep scrolling to learn more! 

Click to jump ahead:

10 Essential data presentation examples + methods you should know

What should be included in a data presentation, what are some common mistakes to avoid when presenting data, faqs on data presentation examples, transform your message with impactful data storytelling.

Data presentation is a vital skill in today’s information-driven world. Whether you’re in business, academia, or simply want to convey information effectively, knowing the different ways of presenting data is crucial. For impactful data storytelling, consider these essential data presentation methods:

1. Bar graph

Ideal for comparing data across categories or showing trends over time.

Bar graphs, also known as bar charts are workhorses of data presentation. They’re like the Swiss Army knives of visualization methods because they can be used to compare data in different categories or display data changes over time. 

In a bar chart, categories are displayed on the x-axis and the corresponding values are represented by the height of the bars on the y-axis. 

It’s a straightforward and effective way to showcase raw data, making it a staple in business reports, academic presentations and beyond.

Make sure your bar charts are concise with easy-to-read labels. Whether your bars go up or sideways, keep it simple by not overloading with too many categories.

2. Line graph

Great for displaying trends and variations in data points over time or continuous variables.

Line charts or line graphs are your go-to when you want to visualize trends and variations in data sets over time.

One of the best quantitative data presentation examples, they work exceptionally well for showing continuous data, such as sales projections over the last couple of years or supply and demand fluctuations. 

The x-axis represents time or a continuous variable and the y-axis represents the data values. By connecting the data points with lines, you can easily spot trends and fluctuations.

A tip when presenting data with line charts is to minimize the lines and not make it too crowded. Highlight the big changes, put on some labels and give it a catchy title.

3. Pie chart

Useful for illustrating parts of a whole, such as percentages or proportions.

Pie charts are perfect for showing how a whole is divided into parts. They’re commonly used to represent percentages or proportions and are great for presenting survey results that involve demographic data. 

Each “slice” of the pie represents a portion of the whole and the size of each slice corresponds to its share of the total. 

While pie charts are handy for illustrating simple distributions, they can become confusing when dealing with too many categories or when the differences in proportions are subtle.

Don’t get too carried away with slices — label those slices with percentages or values so people know what’s what and consider using a legend for more categories.

4. Scatter plot

Effective for showing the relationship between two variables and identifying correlations.

Scatter plots are all about exploring relationships between two variables. They’re great for uncovering correlations, trends or patterns in data. 

In a scatter plot, every data point appears as a dot on the chart, with one variable marked on the horizontal x-axis and the other on the vertical y-axis.

By examining the scatter of points, you can discern the nature of the relationship between the variables, whether it’s positive, negative or no correlation at all.

If you’re using scatter plots to reveal relationships between two variables, be sure to add trendlines or regression analysis when appropriate to clarify patterns. Label data points selectively or provide tooltips for detailed information.

5. Histogram

Best for visualizing the distribution and frequency of a single variable.

Histograms are your choice when you want to understand the distribution and frequency of a single variable. 

They divide the data into “bins” or intervals and the height of each bar represents the frequency or count of data points falling into that interval. 

Histograms are excellent for helping to identify trends in data distributions, such as peaks, gaps or skewness.

Here’s something to take note of — ensure that your histogram bins are appropriately sized to capture meaningful data patterns. Using clear axis labels and titles can also help explain the distribution of the data effectively.

6. Stacked bar chart

Useful for showing how different components contribute to a whole over multiple categories.

Stacked bar charts are a handy choice when you want to illustrate how different components contribute to a whole across multiple categories. 

Each bar represents a category and the bars are divided into segments to show the contribution of various components within each category. 

This method is ideal for highlighting both the individual and collective significance of each component, making it a valuable tool for comparative analysis.

Stacked bar charts are like data sandwiches—label each layer so people know what’s what. Keep the order logical and don’t forget the paintbrush for snazzy colors. Here’s a data analysis presentation example on writers’ productivity using stacked bar charts:

7. Area chart

Similar to line charts but with the area below the lines filled, making them suitable for showing cumulative data.

Area charts are close cousins of line charts but come with a twist. 

Imagine plotting the sales of a product over several months. In an area chart, the space between the line and the x-axis is filled, providing a visual representation of the cumulative total. 

This makes it easy to see how values stack up over time, making area charts a valuable tool for tracking trends in data.

For area charts, use them to visualize cumulative data and trends, but avoid overcrowding the chart. Add labels, especially at significant points and make sure the area under the lines is filled with a visually appealing color gradient.

8. Tabular presentation

Presenting data in rows and columns, often used for precise data values and comparisons.

Tabular data presentation is all about clarity and precision. Think of it as presenting numerical data in a structured grid, with rows and columns clearly displaying individual data points. 

A table is invaluable for showcasing detailed data, facilitating comparisons and presenting numerical information that needs to be exact. They’re commonly used in reports, spreadsheets and academic papers.

When presenting tabular data, organize it neatly with clear headers and appropriate column widths. Highlight important data points or patterns using shading or font formatting for better readability.

9. Textual data

Utilizing written or descriptive content to explain or complement data, such as annotations or explanatory text.

Textual data presentation may not involve charts or graphs, but it’s one of the most used qualitative data presentation examples. 

It involves using written content to provide context, explanations or annotations alongside data visuals. Think of it as the narrative that guides your audience through the data. 

Well-crafted textual data can make complex information more accessible and help your audience understand the significance of the numbers and visuals.

Textual data is your chance to tell a story. Break down complex information into bullet points or short paragraphs and use headings to guide the reader’s attention.

10. Pictogram

Using simple icons or images to represent data is especially useful for conveying information in a visually intuitive manner.

Pictograms are all about harnessing the power of images to convey data in an easy-to-understand way. 

Instead of using numbers or complex graphs, you use simple icons or images to represent data points. 

For instance, you could use a thumbs up emoji to illustrate customer satisfaction levels, where each face represents a different level of satisfaction. 

Pictograms are great for conveying data visually, so choose symbols that are easy to interpret and relevant to the data. Use consistent scaling and a legend to explain the symbols’ meanings, ensuring clarity in your presentation.

Looking for more data presentation ideas? Use the Venngage graph maker or browse through our gallery of chart templates to pick a template and get started! 

A comprehensive data presentation should include several key elements to effectively convey information and insights to your audience. Here’s a list of what should be included in a data presentation:

1. Title and objective

• Begin with a clear and informative title that sets the context for your presentation.
• State the primary objective or purpose of the presentation to provide a clear focus.

2. Key data points

• Present the most essential data points or findings that align with your objective.
• Use charts, graphical presentations or visuals to illustrate these key points for better comprehension.

3. Context and significance

• Provide a brief overview of the context in which the data was collected and why it’s significant.
• Explain how the data relates to the larger picture or the problem you’re addressing.

4. Key takeaways

• Summarize the main insights or conclusions that can be drawn from the data.
• Highlight the key takeaways that the audience should remember.

5. Visuals and charts

• Use clear and appropriate visual aids to complement the data.
• Ensure that visuals are easy to understand and support your narrative.

6. Implications or actions

• Discuss the practical implications of the data or any recommended actions.
• If applicable, outline next steps or decisions that should be taken based on the data.

7. Q&A and discussion

• Allocate time for questions and open discussion to engage the audience.
• Address queries and provide additional insights or context as needed.

Presenting data is a crucial skill in various professional fields, from business to academia and beyond. To ensure your data presentations hit the mark, here are some common mistakes that you should steer clear of:

Overloading with data

Presenting too much data at once can overwhelm your audience. Focus on the key points and relevant information to keep the presentation concise and focused. Here are some free data visualization tools you can use to convey data in an engaging and impactful way. 

Assuming everyone’s on the same page

It’s easy to assume that your audience understands as much about the topic as you do. But this can lead to either dumbing things down too much or diving into a bunch of jargon that leaves folks scratching their heads. Take a beat to figure out where your audience is coming from and tailor your presentation accordingly.

Misleading visuals

Using misleading visuals, such as distorted scales or inappropriate chart types can distort the data’s meaning. Pick the right data infographics and understandable charts to ensure that your visual representations accurately reflect the data.

Not providing context

Data without context is like a puzzle piece with no picture on it. Without proper context, data may be meaningless or misinterpreted. Explain the background, methodology and significance of the data.

Not citing sources properly

Neglecting to cite sources and provide citations for your data can erode its credibility. Always attribute data to its source and utilize reliable sources for your presentation.

Not telling a story

Avoid simply presenting numbers. If your presentation lacks a clear, engaging story that takes your audience on a journey from the beginning (setting the scene) through the middle (data analysis) to the end (the big insights and recommendations), you’re likely to lose their interest.

Infographics are great for storytelling because they mix cool visuals with short and sweet text to explain complicated stuff in a fun and easy way. Create one with Venngage’s free infographic maker to create a memorable story that your audience will remember.

Ignoring data quality

Presenting data without first checking its quality and accuracy can lead to misinformation. Validate and clean your data before presenting it.

Simplify your visuals

Fancy charts might look cool, but if they confuse people, what’s the point? Go for the simplest visual that gets your message across. Having a dilemma between presenting data with infographics v.s data design? This article on the difference between data design and infographics might help you out. 

Missing the emotional connection

Data isn’t just about numbers; it’s about people and real-life situations. Don’t forget to sprinkle in some human touch, whether it’s through relatable stories, examples or showing how the data impacts real lives.

Skipping the actionable insights

At the end of the day, your audience wants to know what they should do with all the data. If you don’t wrap up with clear, actionable insights or recommendations, you’re leaving them hanging. Always finish up with practical takeaways and the next steps.

Can you provide some data presentation examples for business reports?

Business reports often benefit from data presentation through bar charts showing sales trends over time, pie charts displaying market share,or tables presenting financial performance metrics like revenue and profit margins.

What are some creative data presentation examples for academic presentations?

Creative data presentation ideas for academic presentations include using statistical infographics to illustrate research findings and statistical data, incorporating storytelling techniques to engage the audience or utilizing heat maps to visualize data patterns.

What are the key considerations when choosing the right data presentation format?

When choosing a chart format , consider factors like data complexity, audience expertise and the message you want to convey. Options include charts (e.g., bar, line, pie), tables, heat maps, data visualization infographics and interactive dashboards.

Knowing the type of data visualization that best serves your data is just half the battle. Here are some best practices for data visualization to make sure that the final output is optimized. 

How can I choose the right data presentation method for my data?

To select the right data presentation method, start by defining your presentation’s purpose and audience. Then, match your data type (e.g., quantitative, qualitative) with suitable visualization techniques (e.g., histograms, word clouds) and choose an appropriate presentation format (e.g., slide deck, report, live demo).

For more presentation ideas , check out this guide on how to make a good presentation or use a presentation software to simplify the process.  

How can I make my data presentations more engaging and informative?

To enhance data presentations, use compelling narratives, relatable examples and fun data infographics that simplify complex data. Encourage audience interaction, offer actionable insights and incorporate storytelling elements to engage and inform effectively.

The opening of your presentation holds immense power in setting the stage for your audience. To design a presentation and convey your data in an engaging and informative, try out Venngage’s free presentation maker to pick the right presentation design for your audience and topic. 

What is the difference between data visualization and data presentation?

Data presentation typically involves conveying data reports and insights to an audience, often using visuals like charts and graphs. Data visualization , on the other hand, focuses on creating those visual representations of data to facilitate understanding and analysis. 

Now that you’ve learned a thing or two about how to use these methods of data presentation to tell a compelling data story , it’s time to take these strategies and make them your own. 

But here’s the deal: these aren’t just one-size-fits-all solutions. Remember that each example we’ve uncovered here is not a rigid template but a source of inspiration. It’s all about making your audience go, “Wow, I get it now!”

Think of your data presentations as your canvas – it’s where you paint your story, convey meaningful insights and make real change happen. 

So, go forth, present your data with confidence and purpose and watch as your strategic influence grows, one compelling presentation at a time.

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• Presentation of Data

Data Presenting for Clearer Reference

Imagine the statistical data without a definite presentation, will be burdensome! Data presentation is one of the important aspects of Statistics. Presenting the data helps the users to study and explain the statistics thoroughly. We are going to discuss this presentation of data and know-how information is laid down methodically. 

In this context, we are going to present the topic - Presentation of Data which is to be referred to by the students and the same is to be studied in regard to the types of presentations of data. 

Presentation of Data and Information

Statistics is all about data. Presenting data effectively and efficiently is an art. You may have uncovered many truths that are complex and need long explanations while writing. This is where the importance of the presentation of data comes in. You have to present your findings in such a way that the readers can go through them quickly and understand each and every point that you wanted to showcase. As time progressed and new and complex research started happening, people realized the importance of the presentation of data to make sense of the findings.

Define Data Presentation

Data presentation is defined as the process of using various graphical formats to visually represent the relationship between two or more data sets so that an informed decision can be made based on them.

Types of Data Presentation

Broadly speaking, there are three methods of data presentation:

Diagrammatic

Textual Ways of Presenting Data

Out of the different methods of data presentation, this is the simplest one. You just write your findings in a coherent manner and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture. Yes, the introduction, summary, and conclusion can help condense the information.

Tabular Ways of Data Presentation and Analysis

To avoid the complexities involved in the textual way of data presentation, people use tables and charts to present data. In this method, data is presented in rows and columns - just like you see in a cricket match showing who made how many runs. Each row and column have an attribute (name, year, sex, age, and other things like these). It is against these attributes that data is written within a cell.

Diagrammatic Presentation: Graphical Presentation of Data in Statistics

This kind of data presentation and analysis method says a lot with dramatically short amounts of time.

Diagrammatic Presentation has been divided into further categories:

Geometric Diagram

When a Diagrammatic presentation involves shapes like a bar or circle, we call that a Geometric Diagram. Examples of Geometric Diagram

Bar Diagram

Simple Bar Diagram

Simple Bar Diagram is composed of rectangular bars. All of these bars have the same width and are placed at an equal distance from each other. The bars are placed on the X-axis. The height or length of the bars is used as the means of measurement. So, on the Y-axis, you have the measurement relevant to the data. 

Suppose, you want to present the run scored by each batsman in a game in the form of a bar chart. Mark the runs on the Y-axis - in ascending order from the bottom. So, the lowest scorer will be represented in the form of the smallest bar and the highest scorer in the form of the longest bar.

Multiple Bar Diagram

(Image will be uploaded soon)

In many states of India, electric bills have bar diagrams showing the consumption in the last 5 months. Along with these bars, they also have bars that show the consumption that happened in the same months of the previous year. This kind of Bar Diagram is called Multiple Bar Diagrams.

Component Bar Diagram

(image will be uploaded soon)

Sometimes, a bar is divided into two or more parts. For example, if there is a Bar Diagram, the bars of which show the percentage of male voters who voted and who didn’t and the female voters who voted and who didn’t. Instead of creating separate bars for who did and who did not, you can divide one bar into who did and who did not.

A pie chart is a chart where you divide a pie (a circle) into different parts based on the data. Each of the data is first transformed into a percentage and then that percentage figure is multiplied by 3.6 degrees. The result that you get is the angular degree of that corresponding data to be drawn in the pie chart. So, for example, you get 30 degrees as the result, on the pie chart you draw that angle from the center.

Frequency Diagram

Suppose you want to present data that shows how many students have 1 to 2 pens, how many have 3 to 5 pens, how many have 6 to 10 pens (grouped frequency) you do that with the help of a Frequency Diagram. A Frequency Diagram can be of many kinds:

Where the grouped frequency of pens (from the above example) is written on the X-axis and the numbers of students are marked on the Y-axis. The data is presented in the form of bars.

Frequency Polygon

When you join the midpoints of the upper side of the rectangles in a histogram, you get a Frequency Polygon

Frequency Curve

When you draw a freehand line that passes through the points of the Frequency Polygon, you get a Frequency Curve.

Ogive 

Suppose 2 students got 0-20 marks in maths, 5 students got 20-30 marks and 4 students got 30-50 marks in Maths. So how many students got less than 50 marks? Yes, 5+2=7. And how many students got more than 20 marks? 5+4=9. This type of more than and less than data are represented in the form of the ogive. The meeting point of the less than and more than line will give you the Median.

Arithmetic Line Graph

If you want to see the trend of Corona infection vs the number of recoveries from January 2020 to December 2020, you can do that in the form of an Arithmetic Line Graph. The months should be marked on the X-axis and the number of infections and recoveries are marked on the Y-axis. You can compare if the recovery is greater than the infection and if the recovery and infection are going at the same rate or not with the help of this Diagram.

Did You Know?

Sir Ronald Aylmer Fisher is known as the father of modern statistics.

FAQs on Presentation of Data

1. What are the 4 types of Tabular Presentation?

The tabular presentation method can be further divided into 4 categories:

Qualitative

Quantitative

Qualitative classification is done when the attributes in the table are some kind of ‘quality’ or feature. Suppose you want to make a table where you would show how many batsmen made half-centuries and how many batsmen made centuries in IPL 2020. Notice that the data would have only numbers - no age, sex, height is needed. This type of tabulation is called quantitative tabulation.

If you want to make a table that would inform which year’s world cup, which team won. The classifying variable, here, is year or time. This kind of classification is called Temporal classification.

If you want to list the top 5 coldest places in the world. The classifying variable here would be a place in each case. This kind of classification is called Spatial Classification.

2. Are bar charts and histograms the Same?

No, they are not the same. With a histogram, you measure the frequency of quantitative data. With bar charts, you compare categorical data.

3. What is the definition of Data Presentation?

When research work is completed, the data gathered from it can be quite large and complex. Organizing the data in a coherent, easy-to-understand, quick to read and graphical way is called data presentation.

👀 Turn any prompt into captivating visuals in seconds with our AI-powered design generator ✨ Try Piktochart AI!

7 Best Practices to a Standout Research Presentation

After months of rigorous analysis, interpretation, and synthesis, your research findings are ready to change the world (or at least your corner of it). 

Now comes the next challenge: how do you translate your complex insights into a compelling research presentation that not only informs but captivates your audience? 

Keep reading for tips and best practices to create a research presentation as confident as your findings.

Pro tip : Get your free Piktochart account before you scroll down. This way, you can immediately put our tips to practice as you read along. Alternatively, you can hop over to our AI presentation maker and find more examples of professional research presentation decks.

Keep your pen and paper handy so you can take notes!

What exactly happens during a research presentation? 

When you present your research, you share what you’ve been working on and what you found out. 

You start by explaining why your topic matters, then walk your audience through how you went about investigating it. Then, you share your results, often with visuals to make things clear. You wrap up by recapping your main points, talking about what your findings and their relevance, and pointing out any questions that still need to be answered. 

In a nutshell, your research presentation is a way to get your work out there, get people talking, and maybe even gain new perspectives.

How long is a typical research presentation? 

The ideal length of a research presentation depends on the specific context, audience, and purpose. Here’s a general guideline:

• Short and sweet (10-15 minutes): Perfect for giving your audience a taste of your research and sparking their interest.
• Standard fare (20-30 minutes): Enough time to dive deeper into your methods and findings, ideal for most academic settings.
• Deep dive (45-60+ minutes): A comprehensive look at your work. This is best for specialized audiences who want all the details of your research.

How about an AP research presentation? How long should it be?

The official time limit for an AP (Advanced Placement) Research presentation is 15 to 20 minutes. But here’s a quick tip: you won’t want to use every second of that. Effective presenters often aim for the lower end of this range because shorter yet well-organized presentations hold attention and leave room for questions.

Aim for an AP research presentation that’s around 12-15 minutes, leaving a few minutes for questions or discussion. This keeps things engaging and shows you respect your audience’s time. As you’ll see later below, some of the best winning presentations we’ve found online are just 3 minutes long!

Speaking of, let’s get into the nitty-gritty of designing successful, effective research presentations.

Beyond bullet points: How to create research presentations that stand out

First time presenters often fall into the trap of relying on endless bullet points and dry recitations of data. As tempting as this sounds to effectively organize your presentation, it can often look like you’ve just copied and pasted your paper into the slides, and you’ll end up reading off them verbatim.

Here are some best practices with accompanying research presentation examples to help you go beyond bullet points and leave a lasting impression the next time you present your research. 

1. Develop a narrative for your research.

Let’s be honest, nobody wants to sit through a data dump disguised as a presentation. Instead, think of your research as a compelling story. Every good story has the following elements:

• Exposition: Set the scene for your research. What’s the problem you’re tackling? Why is your topic important? Use this section to create a compelling rationale that resonates with your audience’s interests or the broader implications of your work.
• Rising action (The challenge): Build tension and intrigue. What challenges did you face? What unexpected twists and turns did your research take? This is where you describe your research approach and the obstacles encountered, giving you a chance to inject some excitement into the research while demonstrating your problem-solving skills.
• Climax (Results): Reveal your findings! This is the moment your audience has been waiting for. This is the best time to use visuals to make your results memorable.
• Falling Action (Unpacking the results)): Help your audience make sense of your results. What are the broader implications? Are there potential applications, policy impacts, or do the results advance the theoretical understanding in your field?
• Resolution: Wrap it up with a satisfying conclusion. What are the next steps? What questions remain unanswered? End your presentation on a high note. Summarize your key takeaways, offer a call to action, or pose thought-provoking questions for future research. This leaves your audience wanting more.

A great example of a research presentation following a narrative arc is this 3-minute presentation by Shannon Lea Watkins of the University of California San Francisco. It won 1st place (Poster Presentation category) for APPAM’s (Association for Public Analysis and Management) 2017 Fall Research Conference.

The presentation skillfully introduces the research question, “Does initiating tobacco use with flavored products predict current smoking status? An examination by race, gender, and sexual identity,” and builds anticipation for the findings. The subsequent discussion of the research’s implications also effectively engages the audience and highlights its significance. 

In just 3 minutes, the presenter communicated the core message using clear language and highlighted the key takeaways.

2. Use a font size that is legible from a distance.

Imagine your grandmother sitting in the back row. Would she be able to read your slides comfortably?

If not, it’s time to bump up your presentation slide’s font size. A good rule of thumb is to use a minimum font size of 24 points for body text and 36 points for headings.

In addition, white space is your friend. Don’t overcrowd your slides with too much text. Instead, use concise bullet points, phrases, or keywords to guide your narrative. This will keep your audience focused on your story and not squinting to read tiny texts. 

Dr. Oliver Hauser’s presentation of his winning paper on “Minority Report: A Modern Perspective on Reducing Unethical Behavior in Organizations” is a good example of a presentation with legible text. The black text on a white background also creates excellent contrast which makes the text easily readable.

3. Choose your fonts carefully. 

Now that you’ve taken care of your presentations’ font size, let’s talk about font types. So what’s the best font for research presentations? 

When choosing the right font for your research presentation, consider the “personality” of different fonts and choose ones that align with your research’s tone and topic. For example, serif fonts are traditional and classic, while sans serif fonts are modern and clean. 

It also helps to prioritize legibility over style, especially for body text. Finally,  don’t be afraid to mix and match fonts for visual interest.

Here’s a pro tip from Stephanie Lee , Lead Designer at Piktochart: 

“An important factor to consider when choosing fonts to use is to ensure it has good readability. Roboto is a good font to consider for presentations, it’s a reliable font that’s versatile in that it can be used for both headings and body copy. It’s a great option if you need your design to look professional & modern.”

If you want to get creative, consider exploring less common fonts that still maintain readability. Some popular choices include:

• Futura : A geometric sans serif font with a modern feel.
• Raleway : A versatile sans serif font that works well for both headings and body text.
• Libre Baskerville : A classic serif font with excellent readability.
• Poppins : A geometric sans serif font with a friendly and approachable vibe.

Recommended reading : 14 Fonts That Make Your PowerPoint Presentations Stand Out

How about font pairings for presentations?

Here are some general tips to help you with font pairings and create a professional and visually-appealing research presentation:

• Pair a serif font with a sans serif font: This classic combination offers a nice contrast between traditional and modern styles.
• Use a bold or decorative font for headings and a simple font for body text: This creates a clear hierarchy and helps your audience navigate your content.
• Limit your font choices to two or three: Using too many fonts can make your presentation look cluttered and unprofessional.

And here are some popular font pairings you can try when making your own presentation :

Classic and readable

• Heading: Georgia or Merriweather (serif)
• Body: Arial or Helvetica (sans-serif)

This combination is timeless and easy on the eyes. It works well for formal presentations and those with a lot of text.

Modern and clean

• Heading: Montserrat or Lato (sans-serif)
• Body: Open Sans or Roboto (sans-serif)

These fonts are sleek and contemporary. They are suitable for presentations with a minimalist design and those targeting a younger audience.

Creative and engaging

• Heading: Playfair Display or Lobster (serif)
• Body: Raleway or Oswald (sans-serif)

This pairing is visually interesting and can help capture attention. This combo is ideal for creative presentations and those focused on design or storytelling.

With Piktochart, finding the right font for your presentation is very straightforward. You’ve got many options right at your fingertips, and you can even upload your own if you want to make it more custom. This makes it easier to customize your research presentation slides and make them look sharp!

4. Choose a color palette that complements your presentation.

Your presentation slides’ color scheme sets the mood of your presentation and can even influence how your audience perceives your message. Here are some pointers to help you pick the righ t color palette :

Match it to your topic

The colors you choose should reflect the tone of your research. Calming blues and green palette combinations might work for a mental health presentation, while fiery reds and oranges could be better for discussing climate change.

Keep it simple

Don’t overwhelm your audience with a rainbow of colors. Following the rule of 3 is a safe approach; stick to a primary color, a secondary color, and maybe an accent color.

Consider color psychology

The color you choose for your presentation can evoke emotions. For example, blue often signifies trust while green can represent growth.

Here are some more examples to get you started:

• Scientific and academic: Use white, gray, black, with a pop of blue or green.
• Business and corporate: Use blues, grays, and a touch of gold.
• Creative and artistic: Go for vibrant colors like orange, yellow, or turquoise.
• Nonprofit and social Impact: Opt for earthy tones like brown or green, with a warm accent like orange.

If you’re still not sure if you can get your presentation’s color scheme right, Piktochart makes it easier for you with its Color Schemes feature. It allows you to apply a set of colors to your entire presentation slide in one click.

Piktochart offers two types of Color Schemes for your presentations:

• Suggested: These are pre-designed palettes curated by Piktochart’s designers and are available in most templates. Access them by clicking on the “Colors” option in the editor.
• Brand: Business plan users can create custom color schemes with up to six colors. These can be manually created or extracted from an image. To create a brand color scheme, go to “Brand” and click on “Create Brand Color Scheme”.

You can edit both types of color schemes by clicking the pencil icon. 

This AP research presentation by Madeline Hart showcases the link between birth order and overall creativity. 

Notice how Madeline incorporates vivid colors into her slides. Vivid colors like orange and yellow green are associated with creativity, energy, and enthusiasm. By using these colors, Madeline subtly reinforces her presentation’s theme and creates a visually stimulating experience for her audience.

In addition, while Madeline uses pops of color, her overall slide design likely remains clean and uncluttered. This allows her audience to focus on the content without being overwhelmed by excessive visuals or text. 

5. Guide your audience with smooth, engaging transitions

Transitions should enhance, not overpower, your presentation. Smooth transitions between slides can make your presentation feel polished and professional. Avoid abrupt jumps or jarring effects. Use subtle fades, slides, or dissolves to maintain a sense of flow and continuity.  It’s also worth noting that shorter transitions may feel energetic, while longer ones create a thoughtful atmosphere.

The good news is that Piktochart offers a range of slide transitions to improve the flow and visual appeal of your presentation. Here are some transition effects you can try:

• None: A simple, static transition with no animation.
• Default: Piktochart’s standard transition, usually a subtle fade or slide.
• Concave: A unique transition where the previous slide appears to bend inwards as the next slide takes its place.
• Fade: A gradual transition where the previous slide fades out as the next slide fades in.
• Linear: A simple, horizontal slide transition.
• Zoom: A dynamic transition where the next slide appears to zoom in from a distance.

Experiment with these transitions to find what best suits your research presentation. Learn more about these Piktochart transitions.

6. Remember the 5/5/5 Rule

The 5/5/5 Rule in presentation design is a simple yet powerful guideline designed to prevent your slides from becoming overwhelming walls of text. Here’s a breakdown of the rule:

• 5 lines of text: Aim to keep the text on each slide to a maximum of five lines. This helps prevent information overload and ensures that your key points are easily digestible.
• 5 words per line: Limit each line of text to approximately five words. This makes your slides easier to read and prevents your audience from getting lost in long sentences or complex ideas.
• 5 text-heavy slides: Avoid presenting more than five consecutive slides that are predominantly text-based. Break up the monotony with visuals, graphs, or interactive elements to maintain audience engagement.

Can you break the 5/5/5 Rule? Of course! It’s a guideline, not a law.

There may be times when you need to exceed these limits, such as when presenting complex data or detailed information. However, always strive for clarity and conciseness. If you must include a lot of text, consider using bullet points, breaking up the information into multiple slides, or providing handouts for your audience to reference later.

7. Test your presentation slides on different devices

Your meticulously crafted presentation might look flawless on your laptop screen, but that doesn’t guarantee it will translate well to other viewing environments like on a projector or smartphone.

Testing your slides on various devices is crucial because screen sizes, resolutions, and even operating systems can drastically alter how your presentation appears.

Here’s a quick checklist you can use:

• Your laptop/desktop
• Projector (if using)
• Smartphone (iOS and Android)
• Tablet (iPad or Android)
• Check in both standard and presentation modes.
• Zoom in and out to simulate different viewing distances.
• Test in different web browsers if you’re using online presentation software .
• Get feedback from others viewing your presentation on their devices.

Testing your research presentation on different devices is easy with Piktochart, thanks to its handy share URL feature. With just a few clicks, you can generate a unique link to your presentation and easily share it with colleagues, friends, or anyone else you’d like to get feedback from.

Here’s how it works:

• Create your presentation in Piktochart.
• Click the “Share” button.
• Select “Public on the Web” and click “Copy Link”
• Send the URL to your reviewers.

They can then access your presentation on their own devices and give valuable feedback on how it looks and functions across different screen sizes and platforms. It’s a simple, efficient way to ensure your presentation is polished and accessible to all audiences.

Make impactful research presentations slides with Piktochart

We’ve covered a lot of ground on how to turn your research into a presentation that’ll grab your audience’s attention and leave a lasting impact.

The takeaway here is it’s not just about the facts and figures—it’s about telling a story, being mindful of your fonts, smooth transitions, and keeping things concise. Testing your slides on different devices is a pro move too.

Don’t let your research findings go unnoticed—use Piktochart’s presentation maker to create impactful and thoughtful research presentations. Get your Piktochart free plan if you haven’t yet!

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Data presentation: A comprehensive guide

Learn how to create data presentation effectively and communicate your insights in a way that is clear, concise, and engaging.

Raja Bothra

Building presentations

Hey there, fellow data enthusiast!

Welcome to our comprehensive guide on data presentation.

Whether you're an experienced presenter or just starting, this guide will help you present your data like a pro. We'll dive deep into what data presentation is, why it's crucial, and how to master it. So, let's embark on this data-driven journey together.

What is data presentation?

Data presentation is the art of transforming raw data into a visual format that's easy to understand and interpret. It's like turning numbers and statistics into a captivating story that your audience can quickly grasp. When done right, data presentation can be a game-changer, enabling you to convey complex information effectively.

Why are data presentations important?

Imagine drowning in a sea of numbers and figures. That's how your audience might feel without proper data presentation. Here's why it's essential:

• Clarity : Data presentations make complex information clear and concise.
• Engagement : Visuals, such as charts and graphs, grab your audience's attention.
• Comprehension : Visual data is easier to understand than long, numerical reports.
• Decision-making : Well-presented data aids informed decision-making.
• Impact : It leaves a lasting impression on your audience.

Types of data presentation:

Now, let's delve into the diverse array of data presentation methods, each with its own unique strengths and applications. We have three primary types of data presentation, and within these categories, numerous specific visualization techniques can be employed to effectively convey your data.

1. Textual presentation

Textual presentation harnesses the power of words and sentences to elucidate and contextualize your data. This method is commonly used to provide a narrative framework for the data, offering explanations, insights, and the broader implications of your findings. It serves as a foundation for a deeper understanding of the data's significance.

2. Tabular presentation

Tabular presentation employs tables to arrange and structure your data systematically. These tables are invaluable for comparing various data groups or illustrating how data evolves over time. They present information in a neat and organized format, facilitating straightforward comparisons and reference points.

3. Graphical presentation

Graphical presentation harnesses the visual impact of charts and graphs to breathe life into your data. Charts and graphs are powerful tools for spotlighting trends, patterns, and relationships hidden within the data. Let's explore some common graphical presentation methods:

• Bar charts: They are ideal for comparing different categories of data. In this method, each category is represented by a distinct bar, and the height of the bar corresponds to the value it represents. Bar charts provide a clear and intuitive way to discern differences between categories.
• Pie charts: It excel at illustrating the relative proportions of different data categories. Each category is depicted as a slice of the pie, with the size of each slice corresponding to the percentage of the total value it represents. Pie charts are particularly effective for showcasing the distribution of data.
• Line graphs: They are the go-to choice when showcasing how data evolves over time. Each point on the line represents a specific value at a particular time period. This method enables viewers to track trends and fluctuations effortlessly, making it perfect for visualizing data with temporal dimensions.
• Scatter plots: They are the tool of choice when exploring the relationship between two variables. In this method, each point on the plot represents a pair of values for the two variables in question. Scatter plots help identify correlations, outliers, and patterns within data pairs.

The selection of the most suitable data presentation method hinges on the specific dataset and the presentation's objectives. For instance, when comparing sales figures of different products, a bar chart shines in its simplicity and clarity. On the other hand, if your aim is to display how a product's sales have changed over time, a line graph provides the ideal visual narrative.

Additionally, it's crucial to factor in your audience's level of familiarity with data presentations. For a technical audience, more intricate visualization methods may be appropriate. However, when presenting to a general audience, opting for straightforward and easily understandable visuals is often the wisest choice.

In the world of data presentation, choosing the right method is akin to selecting the perfect brush for a masterpiece. Each tool has its place, and understanding when and how to use them is key to crafting compelling and insightful presentations. So, consider your data carefully, align your purpose, and paint a vivid picture that resonates with your audience.

What to include in data presentation?

When creating your data presentation, remember these key components:

• Data points : Clearly state the data points you're presenting.
• Comparison : Highlight comparisons and trends in your data.
• Graphical methods : Choose the right chart or graph for your data.
• Infographics : Use visuals like infographics to make information more digestible.
• Numerical values : Include numerical values to support your visuals.
• Qualitative information : Explain the significance of the data.
• Source citation : Always cite your data sources.

How to structure an effective data presentation?

Creating a well-structured data presentation is not just important; it's the backbone of a successful presentation. Here's a step-by-step guide to help you craft a compelling and organized presentation that captivates your audience:

1. Know your audience

Understanding your audience is paramount. Consider their needs, interests, and existing knowledge about your topic. Tailor your presentation to their level of understanding, ensuring that it resonates with them on a personal level. Relevance is the key.

2. Have a clear message

Every effective data presentation should convey a clear and concise message. Determine what you want your audience to learn or take away from your presentation, and make sure your message is the guiding light throughout your presentation. Ensure that all your data points align with and support this central message.

3. Tell a compelling story

Human beings are naturally wired to remember stories. Incorporate storytelling techniques into your presentation to make your data more relatable and memorable. Your data can be the backbone of a captivating narrative, whether it's about a trend, a problem, or a solution. Take your audience on a journey through your data.

4. Leverage visuals

Visuals are a powerful tool in data presentation. They make complex information accessible and engaging. Utilize charts, graphs, and images to illustrate your points and enhance the visual appeal of your presentation. Visuals should not just be an accessory; they should be an integral part of your storytelling.

5. Be clear and concise

Avoid jargon or technical language that your audience may not comprehend. Use plain language and explain your data points clearly. Remember, clarity is king. Each piece of information should be easy for your audience to digest.

6. Practice your delivery

Practice makes perfect. Rehearse your presentation multiple times before the actual delivery. This will help you deliver it smoothly and confidently, reducing the chances of stumbling over your words or losing track of your message.

A basic structure for an effective data presentation

Armed with a comprehensive comprehension of how to construct a compelling data presentation, you can now utilize this fundamental template for guidance:

In the introduction, initiate your presentation by introducing both yourself and the topic at hand. Clearly articulate your main message or the fundamental concept you intend to communicate.

Moving on to the body of your presentation, organize your data in a coherent and easily understandable sequence. Employ visuals generously to elucidate your points and weave a narrative that enhances the overall story. Ensure that the arrangement of your data aligns with and reinforces your central message.

As you approach the conclusion, succinctly recapitulate your key points and emphasize your core message once more. Conclude by leaving your audience with a distinct and memorable takeaway, ensuring that your presentation has a lasting impact.

Additional tips for enhancing your data presentation

To take your data presentation to the next level, consider these additional tips:

• Consistent design : Maintain a uniform design throughout your presentation. This not only enhances visual appeal but also aids in seamless comprehension.
• High-quality visuals : Ensure that your visuals are of high quality, easy to read, and directly relevant to your topic.
• Concise text : Avoid overwhelming your slides with excessive text. Focus on the most critical points, using visuals to support and elaborate.
• Anticipate questions : Think ahead about the questions your audience might pose. Be prepared with well-thought-out answers to foster productive discussions.

By following these guidelines, you can structure an effective data presentation that not only informs but also engages and inspires your audience. Remember, a well-structured presentation is the bridge that connects your data to your audience's understanding and appreciation.

Do’s and don'ts on a data presentation

• Use visuals : Incorporate charts and graphs to enhance understanding.
• Keep it simple : Avoid clutter and complexity.
• Highlight key points : Emphasize crucial data.
• Engage the audience : Encourage questions and discussions.
• Practice : Rehearse your presentation.

Don'ts:

• Overload with data : Less is often more; don't overwhelm your audience.
• Fit Unrelated data : Stay on topic; don't include irrelevant information.
• Neglect the audience : Ensure your presentation suits your audience's level of expertise.
• Read word-for-word : Avoid reading directly from slides.
• Lose focus : Stick to your presentation's purpose.

Summarizing key takeaways

• Definition : Data presentation is the art of visualizing complex data for better understanding.
• Importance : Data presentations enhance clarity, engage the audience, aid decision-making, and leave a lasting impact.
• Types : Textual, Tabular, and Graphical presentations offer various ways to present data.
• Choosing methods : Select the right method based on data, audience, and purpose.
• Components : Include data points, comparisons, visuals, infographics, numerical values, and source citations.
• Structure : Know your audience, have a clear message, tell a compelling story, use visuals, be concise, and practice.
• Do's and don'ts : Do use visuals, keep it simple, highlight key points, engage the audience, and practice. Don't overload with data, include unrelated information, neglect the audience's expertise, read word-for-word, or lose focus.

FAQ's on a data presentation

1. what is data presentation, and why is it important in 2024.

Data presentation is the process of visually representing data sets to convey information effectively to an audience. In an era where the amount of data generated is vast, visually presenting data using methods such as diagrams, graphs, and charts has become crucial. By simplifying complex data sets, presentation of the data may helps your audience quickly grasp much information without drowning in a sea of chart's, analytics, facts and figures.

2. What are some common methods of data presentation?

There are various methods of data presentation, including graphs and charts, histograms, and cumulative frequency polygons. Each method has its strengths and is often used depending on the type of data you're using and the message you want to convey. For instance, if you want to show data over time, try using a line graph. If you're presenting geographical data, consider to use a heat map.

3. How can I ensure that my data presentation is clear and readable?

To ensure that your data presentation is clear and readable, pay attention to the design and labeling of your charts. Don't forget to label the axes appropriately, as they are critical for understanding the values they represent. Don't fit all the information in one slide or in a single paragraph. Presentation software like Prezent and PowerPoint can help you simplify your vertical axis, charts and tables, making them much easier to understand.

4. What are some common mistakes presenters make when presenting data?

One common mistake is trying to fit too much data into a single chart, which can distort the information and confuse the audience. Another mistake is not considering the needs of the audience. Remember that your audience won't have the same level of familiarity with the data as you do, so it's essential to present the data effectively and respond to questions during a Q&A session.

5. How can I use data visualization to present important data effectively on platforms like LinkedIn?

When presenting data on platforms like LinkedIn, consider using eye-catching visuals like bar graphs or charts. Use concise captions and e.g., examples to highlight the single most important information in your data report. Visuals, such as graphs and tables, can help you stand out in the sea of textual content, making your data presentation more engaging and shareable among your LinkedIn connections.

Create your data presentation with prezent

Prezent can be a valuable tool for creating data presentations. Here's how Prezent can help you in this regard:

• Time savings : Prezent saves up to 70% of presentation creation time, allowing you to focus on data analysis and insights.
• On-brand consistency : Ensure 100% brand alignment with Prezent's brand-approved designs for professional-looking data presentations.
• Effortless collaboration : Real-time sharing and collaboration features make it easy for teams to work together on data presentations.
• Data storytelling : Choose from 50+ storylines to effectively communicate data insights and engage your audience.
• Personalization : Create tailored data presentations that resonate with your audience's preferences, enhancing the impact of your data.

In summary, Prezent streamlines the process of creating data presentations by offering time-saving features, ensuring brand consistency, promoting collaboration, and providing tools for effective data storytelling. Whether you need to present data to clients, stakeholders, or within your organization, Prezent can significantly enhance your presentation-making process.

So, go ahead, present your data with confidence, and watch your audience be wowed by your expertise.

Thank you for joining us on this data-driven journey. Stay tuned for more insights, and remember, data presentation is your ticket to making numbers come alive! Sign up for our free trial or book a demo ! ‍

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Buttoning up research: How to present and visualize qualitative data

15 Minute Read

There is no doubt that data visualization is an important part of the qualitative research process. Whether you're preparing a presentation or writing up a report, effective visualizations can help make your findings clear and understandable for your audience. 

In this blog post, we'll discuss some tips for creating effective visualizations of qualitative data. 

First, let's take a closer look at what exactly qualitative data is.

What is qualitative data?

Qualitative data is information gathered through observation, questionnaires, and interviews. It's often subjective, meaning that the researcher has to interpret it to draw meaningful conclusions from it. 

The difference between qualitative data and quantitative data

When researchers use the terms qualitative and quantitative, they're referring to two different types of data. Qualitative data is subjective and descriptive, while quantitative data is objective and numerical.

Qualitative data is often used in research involving psychology or sociology. This is usually where a researcher may be trying to identify patterns or concepts related to people's behavior or attitudes. It may also be used in research involving economics or finance, where the focus is on numerical values such as price points or profit margins. 

Before we delve into how best to present and visualize qualitative data, it's important that we highlight how to be gathering this data in the first place. ‍

How best to gather qualitative data

In order to create an effective visualization of qualitative data, ensure that the right kind of information has been gathered. 

Here are six ways to gather the most accurate qualitative data:

• Define your research question: What data is being set out to collect? A qualitative research question is a definite or clear statement about a condition to be improved, a project’s area of concern, a troubling question that exists, or a difficulty to be eliminated. It not only defines who the participants will be but guides the data collection methods needed to achieve the most detailed responses.
• ‍ Determine the best data collection method(s): The data collected should be appropriate to answer the research question. Some common qualitative data collection methods include interviews, focus groups, observations, or document analysis. Consider the strengths and weaknesses of each option before deciding which one is best suited to answer the research question.  ‍
• Develop a cohesive interview guide: Creating an interview guide allows researchers to ask more specific questions and encourages thoughtful responses from participants. It’s important to design questions in such a way that they are centered around the topic of discussion and elicit meaningful insight into the issue at hand. Avoid leading or biased questions that could influence participants’ answers, and be aware of cultural nuances that may affect their answers.
• ‍ Stay neutral – let participants share their stories: The goal is to obtain useful information, not to influence the participant’s answer. Allowing participants to express themselves freely will help to gather more honest and detailed responses. It’s important to maintain a neutral tone throughout interviews and avoid judgment or opinions while they are sharing their story. 
• ‍ Work with at least one additional team member when conducting qualitative research: Participants should always feel comfortable while providing feedback on a topic, so it can be helpful to have an extra team member present during the interview process – particularly if this person is familiar with the topic being discussed. This will ensure that the atmosphere of the interview remains respectful and encourages participants to speak openly and honestly.
• ‍ Analyze your findings: Once all of the data has been collected, it’s important to analyze it in order to draw meaningful conclusions. Use tools such as qualitative coding or content analysis to identify patterns or themes in the data, then compare them with prior research or other data sources. This will help to draw more accurate and useful insights from the results. 

By following these steps, you will be well-prepared to collect and analyze qualitative data for your research project. Next, let's focus on how best to present the qualitative data that you have gathered and analyzed.

Create your own AI-powered templates for better, faster research synthesis. Discover new customer insights from data instantly.

The top 10 things Notably shipped in 2023 and themes for 2024.

How to visually present qualitative data.

When it comes to how to present qualitative data visually, the goal is to make research findings clear and easy to understand. To do this, use visuals that are both attractive and informative. 

Presenting qualitative data visually helps to bring the user’s attention to specific items and draw them into a more in-depth analysis. Visuals provide an efficient way to communicate complex information, making it easier for the audience to comprehend. 

Additionally, visuals can help engage an audience by making a presentation more interesting and interactive.

Here are some tips for creating effective visuals from qualitative data:

• ‍ Choose the right type of visualization: Consider which type of visual would best convey the story that is being told through the research. For example, bar charts or line graphs might be appropriate for tracking changes over time, while pie charts or word clouds could help show patterns in categorical data. 
• ‍ Include contextual information: In addition to showing the actual numbers, it's helpful to include any relevant contextual information in order to provide context for the audience. This can include details such as the sample size, any anomalies that occurred during data collection, or other environmental factors.
• ‍ Make it easy to understand: Always keep visuals simple and avoid adding too much detail or complexity. This will help ensure that viewers can quickly grasp the main points without getting overwhelmed by all of the information. 
• ‍ Use color strategically: Color can be used to draw attention to certain elements in your visual and make it easier for viewers to find the most important parts of it. Just be sure not to use too many different colors, as this could create confusion instead of clarity. 
• ‍ Use charts or whiteboards: Using charts or whiteboards can help to explain the data in more detail and get viewers engaged in a discussion. This type of visual tool can also be used to create storyboards that illustrate the data over time, helping to bring your research to life. 

Visualizing qualitative data in Notably

Notably helps researchers visualize their data on a flexible canvas, charts, and evidence based insights. As an all-in-one research platform, Notably enables researchers to collect, analyze and present qualitative data effectively.

Notably provides an intuitive interface for analyzing data from a variety of sources, including interviews, surveys, desk research, and more. Its powerful analytics engine then helps you to quickly identify insights and trends in your data . Finally, the platform makes it easy to create beautiful visuals that will help to communicate research findings with confidence. 

Research Frameworks in Analysis

The canvas in Analysis is a multi-dimensional workspace to play with your data spatially to find likeness and tension. Here, you may use a grounded theory approach to drag and drop notes into themes or patterns that emerge in your research. Utilizing the canvas tools such as shapes, lines, and images, allows researchers to build out frameworks such as journey maps, empathy maps, 2x2's, etc. to help synthesize their data.

Going one step further, you may begin to apply various lenses to this data driven canvas. For example, recoloring by sentiment shows where pain points may distributed across your customer journey. Or, recoloring by participant may reveal if one of your participants may be creating a bias towards a particular theme.

Exploring Qualitative Data through a Quantitative Lens

Once you have begun your analysis, you may visualize your qualitative data in a quantitative way through charts. You may choose between a pie chart and or a stacked bar chart to visualize your data. From here, you can segment your data to break down the ‘bar’ in your bar chart and slices in your pie chart one step further.

To segment your data, you can choose between ‘Tag group’, ‘Tag’, ‘Theme’, and ‘Participant'. Each group shows up as its own bar in the bar chart or slice in the pie chart. For example, try grouping data as ‘Participant’ to see the volume of notes assigned to each person. Or, group by ‘Tag group’ to see which of your tag groups have the most notes.

Depending on how you’ve grouped or segmented your charts will affect the options available to color your chart. Charts use colors that are a mix of sentiment, tag, theme, and default colors. Consider color as a way of assigning another layer of meaning to your data. For example, choose a red color for tags or themes that are areas of friction or pain points. Use blue for tags that represent opportunities.

AI Powered Insights and Cover Images

One of the most powerful features in Analysis is the ability to generate insights with AI. Insights combine information, inspiration, and intuition to help bridge the gap between knowledge and wisdom. Even before you have any tags or themes, you may generate an AI Insight from your entire data set. You'll be able to choose one of our AI Insight templates that are inspired by trusted design thinking frameworks to stimulate generative, and divergent thinking. With just the click of a button, you'll get an insight that captures the essence and story of your research. You may experiment with a combination of tags, themes, and different templates or, create your own custom AI template. These insights are all evidence-based, and are centered on the needs of real people. You may package these insights up to present your research by embedding videos, quotes and using AI to generate unique cover image.

You can sign up to run an end to end research project for free and receive tips on how to make the most out of your data. Want to chat about how Notably can help your team do better, faster research? Book some time here for a 1:1 demo with your whole team.

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• Presentations

How to Present Data & Numbers in Presentations (Like a Pro)

Data is more important than ever. But do you know how to present data? Your audience needs information in a way that's easy-to-follow. With charts and graphs, data comes to life.

In this tutorial, you'll learn how to present data. The intuitive presentation of data and information is essential so that your point comes across. With our tips, we'll help you take flat data tables and convert them to useful and explanatory charts.

Why Present Data and Numbers With Charts?

Often, you’ll find yourself presenting data in PowerPoint. It’s a useful tool to illustrate data and bring numbers to life. But if you go about it the wrong way, you’ll distract and confuse your audience. Remember, the goal of sharing data is to deliver insights.

When you think of how to present data, you've got several options. Words alone should be an automatic no-no. Clustering numerical data in text paragraphs will confuse an audience. Similarly, tables don’t go far enough.

Consider the example below. While this approach may work for a simple dataset, it’s hard to capture value insights at a glance. Keep in mind, you want a viewer to quickly grasp the fundamental meaning of the data instantly.

That’s why your best option is to present data and numbers with charts. These are two related ways to present data that take a truly visual approach. Charts and graphs are forms of infographics. An infographic is a visual illustration meant to show ideas. They look great, they're easy to read, and they work.

Recent research vividly shows their effectiveness. Infographics are read at a rate of 30:1 over text articles. Pair this with the fact that visual information represents 90% of what transmits to a reader’s brain . Clearly, these are tools to keep in your wheelhouse.

As you can see below, the table data above transforms from a complex table to a clear and concise visual. It’s the identical range of data! The magic happens in the display of it. Charts are the key to success in the presentation of data and information.

How to Present Data and Numbers in Presentations

We’ve learned that the best way to present data is with charts. Now that you’re armed with this knowledge, you've got many options to choose from.

Premium PowerPoint data presentation templates are your best friend. These take the hard work out of building and sharing data charts. They teach you how to present data in presentations with pre-built options. All you need is your dataset!

For our walkthrough tutorial, we’ll use the Chart Presentation template from Envato Elements. It’s a premium option with 24 custom slide designs inside. Each is easy to customize to meet your data presentation needs.

With the template downloaded and opened in PowerPoint, let’s get to work learning how to present data. Follow the principles below, and you’ll be ready to get started!

1. Assess Your Data

Charts come in all shapes and sizes. There are pie charts, column charts, line charts, and many more. All have many uses, but each is targeted towards different types of data. First, you’ll want to assess the data that you have, and how it would best be presented visually. Let’s work with a sample dataset like the one below.

As you can see, the data has several rows, each representing a different country. Beside these are three columns, each covering sales for a given year. In short, you’re looking at three years of sales forecasts for five countries.

Reading over the data, it’s tough to instantly gain any insights. Sure, if you look long enough, trends start to emerge. But this is a slow, manual process. And imagine if there were fifty countries and twelve years, for example!

Manual analysis would become nearly impossible in a presentation setting. But by using a chart, you can instantly illustrate trends and forecasts. Any viewer – even an untrained eye – can readily see all key points with a moment’s glance.

2. Choose a Visual

Now that you’ve analyzed your data, you can easily see that a chart is essential. But what kind? We briefly mentioned three styles of charts. When you think of how to present data in presentation form, the trick is to choose the style that best fits your data.

For our example, we’re looking at multiple data points for several categories. Here, these data points are three sales values, for five countries each. Keep these ideas for how to present numbers in mind:

• A logical visual would group each country together.
• Then, show each of the three sales figures side by side.
• You could also reverse it – group the years and show sales for all five countries.

In a case like this, a column chart is the ideal choice. These group data just as described.

But when might a different chart type be useful? Imagine if your data included details about Germany’s 2024 sales, for example. Suppose you’re presenting to your marketing team, and they’ve asked how sales of each individual product make up the total. Here, a pie chart would be the perfect option. These show how individual pieces form a whole.

But in this case, we’ve decided on a column chart. Find one in the deck, and let’s insert it. In our template, slide #15 contains a beautiful chart. It’s already built. All you need to do is add your own data.

To do that, click into the chart area, then right-click. From the menu, choose Edit Data. You’ll see an embedded Microsoft Excel spreadsheet launch right inside of PowerPoint. From here, you can simply replace the existing data with the table you already have. As you work, the chart instantly updates itself to match the new data.

In moments, you’ll be presenting data in PowerPoint with this beautiful chart!

3. Style Your Visual

With your chart placed on the slide, you now have an array of design options. Remember, the goal is to make the chart work perfectly for your own data. These options primarily live on the Chart Design menu, which you can find on PowerPoint’s ribbon. With the chart selected, click on Chart Design.

The template has a beautiful color palette, but you can add your own. It helps to choose a color profile with plenty of contrast. This makes your visual even clearer and easier to read.

To add a new palette, click on the Change Colors drop-down menu. You’ll see an array of color swatches display. Click on one, and it'll apply to your chart.

You can add a new background by launching the Chart Styles section in the center of the Chart Design menu. For example, you can choose one with a gray background to make the colors really stand out on the slide.

Also, it’s possible to add more context to the data. The horizontal axis in our example is clear enough, listing countries. But there isn’t any explanation of what the vertical axis represents, or the colorful bars. Follow these steps:

• Open the Add Chart Element dropdown near the upper left of the ribbon.
• Click  Axis Titles.
• Choose Primary Vertical.
• You’ll see Axis Title appear on the chart. This is a text box, which you can select and type into.

Finally, back on the Add Chart Element dropdown, choose Legend , and pick a location like Top . Three colorful squares listing the three years shown in the chart will be added to the drawing. These labels aid in the presentation of data and information.

It’s easy to see how to present numbers in chart form, using PowerPoint. Start with a premium template like this, and then customize the chart inside to fit your needs.

4. Add Notes Where Needed

You now know well that charts are the best way to present data. But they don’t have to stand on their own!

Often, it’s useful to add more context. Audiences may understand the data perfectly but have questions. For example: Why are sales for one country climbing, while they are falling in another?

By adding notes where needed, you can add supporting details. It’s best to keep these off of the chart itself. If you clutter up your visual, the value of it diminishes rapidly. Check out an improved example below.

On our slide example, the paragraph section on the left may become a series of quick bullet points. These add supporting details that more fully explain the data shown in the chart.

Again, you may not always need to do this. But never think that a chart must be all-encompassing, explaining every piece of information by itself. The trick is to boost understanding, while remaining clear and concise.

5. Consider an Appendix

You may have extra details that you need to include in your slides.

In our example, imagine that you've got three sales offices in each of the five countries featured. Each of the fifteen makes up a certain percentage of overall sales. This may be key data for your audience, but it would complicate the visual that you just created.

Here, it’s a good idea to add an appendix. An appendix (often at the end of your slide deck) includes more detailed data. You might not review it with a live audience, but they can look at it later in a handout or digital format.

To add an appendix, go to the end of your presentation, and click New Slide on the Home tab. Here, it might be appropriate to share the detailed data in the form of a table. Or, you can add a pie chart, suitable for this style of dataset.

To add a chart from scratch, go to the Insert tab, then choose Chart > Pie. The embedded Excel window will return, and again, you can insert your data.

An appendix may not always be necessary. But you should include one (or more) if you've got meaningful data that you aren’t placing into the main slide deck.

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Elements is an unbeatable offer because of the unlimited flexibility. With premium templates, you gain access to powerful features not found in free designs:

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The advantages are many. You save hard work, by leaving the slide design tasks to experts. This gives you the time needed to refine your message. Plus, the finished product will wow any audience, thanks to the expertly-crafted graphics . Truly, Envato Elements is the best value for creatives today.

Need a template, but don't want an unlimited subscription? We've got you covered with templates from GraphicRiver . You'll pay-as-you-go, and these templates give you everything you need. They've got pre-made designs for the best way to present data with less work than ever before.

Now Practice the Best Way to Present Data in Presentations

You just learned new ways to present data. Essentially, you saw how to present data in presentations so that your audience  can understand it. Great presenters think of the audience first. They'll thank you for your thoughtful work in how to present numbers and more.

Now, it's your turn! Put these tips on how to present data in presentations to work. Take a flat table in a presentation and convert it with our tips for presenting data in PowerPoint. Just download a template and get started. 

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How To Present Research Data?

Tong seng fah.

MMed (FamMed UKM), Department of Family Medicine, Universiti Kebangsaan Malaysia

Aznida Firzah Abdul Aziz

Introduction.

The result section of an original research paper provides answer to this question “What was found?” The amount of findings generated in a typical research project is often much more than what medical journal can accommodate in one article. So, the first thing the author needs to do is to make a selection of what is worth presenting. Having decided that, he/she will need to convey the message effectively using a mixture of text, tables and graphics. The level of details required depends a great deal on the target audience of the paper. Hence it is important to check the requirement of journal we intend to send the paper to (e.g. the Uniform Requirements for Manuscripts Submitted to Medical Journals 1 ). This article condenses some common general rules on the presentation of research data that we find useful.

SOME GENERAL RULES

• Keep it simple. This golden rule seems obvious but authors who have immersed in their data sometime fail to realise that readers are lost in the mass of data they are a little too keen to present. Present too much information tends to cloud the most pertinent facts that we wish to convey.
• First general, then specific. Start with response rate and description of research participants (these information give the readers an idea of the representativeness of the research data), then the key findings and relevant statistical analyses.
• Data should answer the research questions identified earlier.
• Leave the process of data collection to the methods section. Do not include any discussion. These errors are surprising quite common.
• Always use past tense in describing results.
• Text, tables or graphics? These complement each other in providing clear reporting of research findings. Do not repeat the same information in more than one format. Select the best method to convey the message.

Consider these two lines:

• Mean baseline HbA 1c of 73 diabetic patients before intervention was 8.9% and mean HbA 1c after intervention was 7.8%.
• Mean HbA 1c of 73 of diabetic patients decreased from 8.9% to 7.8% after an intervention.

In line 1, the author presents only the data (i.e. what exactly was found in a study) but the reader is forced to analyse and draw their own conclusion (“mean HbA 1c decreased”) thus making the result more difficult to read. In line 2, the preferred way of writing, the data was presented together with its interpretation.

• Data, which often are numbers and figures, are better presented in tables and graphics, while the interpretation are better stated in text. By doing so, we do not need to repeat the values of HbA 1c in the text (which will be illustrated in tables or graphics), and we can interpret the data for the readers. However, if there are too few variables, the data can be easily described in a simple sentence including its interpretation. For example, the majority of diabetic patients enrolled in the study were male (80%) compare to female (20%).
• Using qualitative words to attract the readers’ attention is not helpful. Such words like “remarkably” decreased, “extremely” different and “obviously” higher are redundant. The exact values in the data will show just how remarkable, how extreme and how obvious the findings are.

“It is clearly evident from Figure 1B that there was significant different (p=0.001) in HbA 1c level at 6, 12 and 18 months after diabetic self-management program between 96 patients in intervention group and 101 patients in control group, but no difference seen from 24 months onwards.” [Too wordy]

Changes of HbA 1c level after diabetic self-management program.

The above can be rewritten as:

“Statistical significant difference was only observed at 6, 12 and 18 months after diabetic self-management program between intervention and control group (Fig 1B)”. [The p values and numbers of patients are already presented in Figure 1B and need not be repeated.]

• Avoid redundant words and information. Do not repeat the result within the text, tables and figures. Well-constructed tables and graphics should be self-explanatory, thus detailed explanation in the text is not required. Only important points and results need to be highlighted in the text.

Tables are useful to highlight precise numerical values; proportions or trends are better illustrated with charts or graphics. Tables summarise large amounts of related data clearly and allow comparison to be made among groups of variables. Generally, well-constructed tables should be self explanatory with four main parts: title, columns, rows and footnotes.

• Title. Keep it brief and relate clearly the content of the table. Words in the title should represent and summarise variables used in the columns and rows rather than repeating the columns and rows’ titles. For example, “Comparing full blood count results among different races” is clearer and simpler than “Comparing haemoglobin, platelet count, and total white cell count among Malays, Chinese and Indians”.

*WC, waist circumference (in cm)

†SBP, systolic blood pressure (in mmHg)

‡DBP, diastolic blood pressure (in mmHg)

£LDL-cholesterol (in mmol/L)

*Odds ratio (95% confidence interval)

†p=0.04

‡p=0.01

• Footnotes. These add clarity to the data presented. They are listed at the bottom of tables. Their use is to define unconventional abbreviation, symbols, statistical analysis and acknowledgement (if the table is adapted from a published table). Generally the font size is smaller in the footnotes and follows a sequence of foot note signs (*, †, ‡, §, ‖, ¶, **, ††, # ). 1 These symbols and abbreviation should be standardised in all tables to avoid confusion and unnecessary long list of footnotes. Proper use of footnotes will reduce the need for multiple columns (e.g. replacing a list of p values) and the width of columns (abbreviating waist circumference to WC as in table 1B )
• Consistent use of units and its decimal places. The data on systolic blood pressure in Table 1B is neater than the similar data in Table 1A .
• Arrange date and timing from left to the right.
• Round off the numbers to fewest decimal places possible to convey meaningful precision. Mean systolic blood pressure of 165.1mmHg (as in Table 1B ) does not add much precision compared to 165mmHg. Furthermore, 0.1mmHg does not add any clinical importance. Hence blood pressure is best to round off to nearest 1mmHg.
• Avoid listing numerous zeros, which made comparison incomprehensible. For example total white cell count is best represented with 11.3 ×10 6 /L rather than 11,300,000/L. This way, we only need to write 11.3 in the cell of the table.
• Avoid too many lines in a table. Often it is sufficient to just have three horizontal lines in a table; one below the title; one dividing the column titles and data; one dividing the data and footnotes. Vertical lines are not necessary. It will only make a table more difficult to read (compare Tables 1A and ​ and1B 1B ).
• Standard deviation can be added to show precision of the data in our table. Placement of standard deviation can be difficult to decide. If we place the standard deviation at the side of our data, it allows clear comparison when we read down ( Table 1B ). On the other hand, if we place the standard deviation below our data, it makes comparison across columns easier. Hence, we should decide what we want the readers to compare.
• It is neater and space-saving if we highlight statistically significant finding with an asterisk (*) or other symbols instead of listing down all the p values ( Table 2 ). It is not necessary to add an extra column to report the detail of student-t test or chi-square values.

Graphics are particularly good for demonstrating a trend in the data that would not be apparent in tables. It provides visual emphasis and avoids lengthy text description. However, presenting numerical data in the form of graphs will lose details of its precise values which tables are able to provide. The authors have to decide the best format of getting the intended message across. Is it for data precision or emphasis on a particular trend and pattern? Likewise, if the data is easily described in text, than text will be the preferred method, as it is more costly to print graphics than text. For example, having a nicely drawn age histogram is take up lots of space but carries little extra information. It is better to summarise it as mean ±SD or median depends on whether the age is normally distributed or skewed. Since graphics should be self-explanatory, all information provided has to be clear. Briefly, a well-constructed graphic should have a title, figure legend and footnotes along with the figure. As with the tables, titles should contain words that describe the data succinctly. Define symbols and lines used in legends clearly.

Some general guides to graphic presentation are:

• Bar charts, either horizontal or column bars, are used to display categorical data. Strictly speaking, bar charts with continuous data should be drawn as histograms or line graphs. Usually, data presented in bar charts are better illustrated in tables unless there are important pattern or trends need to be emphasised.

• Line graphs are most appropriate in tracking changing values between variables over a period of time or when the changing values are continuous data. Independent variables (e.g. time) are usually on the X-axis and dependant variables (for example, HbA 1c ) are usually on the Y-axis. The trend of HbA 1c changes is much more apparent with Figure 1B than Figure 1A , and HbA 1c level at any time after intervention can be accurately read in Figure 1B .
• Pie charts should not be used often as any data in a pie chart is better represented in bar charts (if there are specific data trend to be emphasised) or simple text description (if there are only a few variables). A common error is presenting sex distribution of study subjects in a pie chart. It is simpler by just stating % of male or female in text form.
• Patients’ identity in all illustrations, for example pictures of the patients, x-ray films, and investigation results should remain confidential. Use patient’s initials instead of their real names. Cover or blackout the eyes whenever possible. Obtain consent if pictures are used. Highlight and label areas in the illustration, which need emphasis. Do not let the readers search for details in the illustration, which may result in misinterpretation. Remember, we write to avoid misunderstanding whilst maintaining clarity of data.

Papers are often rejected because wrong statistical tests are used or interpreted incorrectly. A simple approach is to consult the statistician early. Bearing in mind that most readers are not statisticians, the reporting of any statistical tests should aim to be understandable by the average audience but sufficiently rigorous to withstand the critique of experts.

• Simple statistic such as mean and standard deviation, median, normality testing is better reported in text. For example, age of group A subjects was normally distributed with mean of 45.4 years old kg (SD=5.6). More complicated statistical tests involving many variables are better illustrated in tables or graphs with their interpretation by text. (See section on Tables).
• We should quote and interpret p value correctly. It is preferable to quote the exact p value, since it is now easily obtained from standard statistical software. This is more so if the p value is statistically not significant, rather just quoting p>0.05 or p=ns. It is not necessary to report the exact p value that is smaller than 0.001 (quoting p<0.001 is sufficient); it is incorrect to report p=0.0000 (as some software apt to report for very small p value).
• We should refrain from reporting such statement: “mean systolic blood pressure for group A (135mmHg, SD=12.5) was higher than group B (130mmHg, SD= 9.8) but did not reach statistical significance (t=4.5, p=0.56).” When p did not show statistical significance (it might be >0.01 or >0.05, depending on which level you would take), it simply means no difference among groups.
• Confidence intervals. It is now preferable to report the 95% confidence intervals (95%CI) together with p value, especially if a hypothesis testing has been performed.

The main core of the result section consists of text, tables and graphics. As a general rule, text provides narration and interpretation of the data presented. Simple data with few categories is better presented in text form. Tables are useful in summarising large amounts of data systemically and graphics should be used to highlight evidence and trends in the data presented. The content of the data presented must match the research questions and objectives of the study in order to give meaning to the data presented. Keep the data and its statistical analyses as simple as possible to give the readers maximal clarity.

Contributor Information

Tong Seng Fah, MMed (FamMed UKM), Department of Family Medicine, Universiti Kebangsaan Malaysia.

Aznida Firzah Abdul Aziz, MMed (FamMed UKM), Department of Family Medicine, Universiti Kebangsaan Malaysia.

FURTHER READINGS

The Ultimate Guide to Qualitative Research - Part 3: Presenting Qualitative Data

• Introduction

How do you present qualitative data?

Data visualization.

• Research paper writing
• Transparency and rigor in research
• How to publish a research paper

Table of contents

• Transparency and rigor

Navigate to other guide parts:

Part 1: The Basics or Part 2: Handling Qualitative Data

• Presenting qualitative data

In the end, presenting qualitative research findings is just as important a skill as mastery of qualitative research methods for the data collection and data analysis process . Simply uncovering insights is insufficient to the research process; presenting a qualitative analysis holds the challenge of persuading your audience of the value of your research. As a result, it's worth spending some time considering how best to report your research to facilitate its contribution to scientific knowledge.

When it comes to research, presenting data in a meaningful and accessible way is as important as gathering it. This is particularly true for qualitative research , where the richness and complexity of the data demand careful and thoughtful presentation. Poorly written research is taken less seriously and left undiscussed by the greater scholarly community; quality research reporting that persuades its audience stands a greater chance of being incorporated in discussions of scientific knowledge.

Qualitative data presentation differs fundamentally from that found in quantitative research. While quantitative data tend to be numerical and easily lend themselves to statistical analysis and graphical representation, qualitative data are often textual and unstructured, requiring an interpretive approach to bring out their inherent meanings. Regardless of the methodological approach , the ultimate goal of data presentation is to communicate research findings effectively to an audience so they can incorporate the generated knowledge into their research inquiry.

As the section on research rigor will suggest, an effective presentation of your research depends on a thorough scientific process that organizes raw data into a structure that allows for a thorough analysis for scientific understanding.

Preparing the data

The first step in presenting qualitative data is preparing the data. This preparation process often begins with cleaning and organizing the data. Cleaning involves checking the data for accuracy and completeness, removing any irrelevant information, and making corrections as needed. Organizing the data often entails arranging the data into categories or groups that make sense for your research framework.

Coding the data

Once the data are cleaned and organized, the next step is coding , a crucial part of qualitative data analysis. Coding involves assigning labels to segments of the data to summarize or categorize them. This process helps to identify patterns and themes in the data, laying the groundwork for subsequent data interpretation and presentation. Qualitative research often involves multiple iterations of coding, creating new and meaningful codes while discarding unnecessary ones , to generate a rich structure through which data analysis can occur.

Uncovering insights

As you navigate through these initial steps, keep in mind the broader aim of qualitative research, which is to provide rich, detailed, and nuanced understandings of people's experiences, behaviors, and social realities. These guiding principles will help to ensure that your data presentation is not only accurate and comprehensive but also meaningful and impactful.

While this process might seem intimidating at first, it's an essential part of any qualitative research project. It's also a skill that can be learned and refined over time, so don't be discouraged if you find it challenging at first. Remember, the goal of presenting qualitative data is to make your research findings accessible and understandable to others. This requires careful preparation, a clear understanding of your data, and a commitment to presenting your findings in a way that respects and honors the complexity of the phenomena you're studying.

In the following sections, we'll delve deeper into how to create a comprehensive narrative from your data, the visualization of qualitative data , and the writing and publication processes . Let's briefly excerpt some of the content in the articles in this part of the guide.

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How often do you read a research article and skip straight to the tables and figures? That's because data visualizations representing qualitative and quantitative data have the power to make large and complex research projects with thousands of data points comprehensible when authors present data to research audiences. Researchers create visual representations to help summarize the data generated from their study and make clear the pathways for actionable insights.

In everyday situations, a picture is always worth a thousand words. Illustrations, figures, and charts convey messages that words alone cannot. In research, data visualization can help explain scientific knowledge, evidence for data insights, and key performance indicators in an orderly manner based on data that is otherwise unstructured.

For all of the various data formats available to researchers, a significant portion of qualitative and social science research is still text-based. Essays, reports, and research articles still rely on writing practices aimed at repackaging research in prose form. This can create the impression that simply writing more will persuade research audiences. Instead, framing research in terms that are easy for your target readers to understand makes it easier for your research to become published in peer-reviewed scholarly journals or find engagement at scholarly conferences. Even in market or professional settings, data visualization is an essential concept when you need to convince others about the insights of your research and the recommendations you make based on the data.

Importance of data visualization

Data visualization is important because it makes it easy for your research audience to understand your data sets and your findings. Also, data visualization helps you organize your data more efficiently. As the explanation of ATLAS.ti's tools will illustrate in this section, data visualization might point you to research inquiries that you might not even be aware of, helping you get the most out of your data. Strictly speaking, the primary role of data visualization is to make the analysis of your data , if not the data itself, clear. Especially in social science research, data visualization makes it easy to see how data scientists collect and analyze data.

Prerequisites for generating data visualizations

Data visualization is effective in explaining research to others only if the researcher or data scientist can make sense of the data in front of them. Traditional research with unstructured data usually calls for coding the data with short, descriptive codes that can be analyzed later, whether statistically or thematically. These codes form the basic data points of a meaningful qualitative analysis . They represent the structure of qualitative data sets, without which a scientific visualization with research rigor would be extremely difficult to achieve. In most respects, data visualization of a qualitative research project requires coding the entire data set so that the codes adequately represent the collected data.

A successfully crafted research study culminates in the writing of the research paper . While a pilot study or preliminary research might guide the research design , a full research study leads to discussion that highlights avenues for further research. As such, the importance of the research paper cannot be overestimated in the overall generation of scientific knowledge.

The physical and natural sciences tend to have a clinical structure for a research paper that mirrors the scientific method: outline the background research, explain the materials and methods of the study, outline the research findings generated from data analysis, and discuss the implications. Qualitative research tends to preserve much of this structure, but there are notable and numerous variations from a traditional research paper that it's worth emphasizing the flexibility in the social sciences with respect to the writing process.

Requirements for research writing

While there aren't any hard and fast rules regarding what belongs in a qualitative research paper , readers expect to find a number of pieces of relevant information in a rigorously-written report. The best way to know what belongs in a full research paper is to look at articles in your target journal or articles that share a particular topic similar to yours and examine how successfully published papers are written.

It's important to emphasize the more mundane but equally important concerns of proofreading and formatting guidelines commonly found when you write a research paper. Research publication shouldn't strictly be a test of one's writing skills, but acknowledging the importance of convincing peer reviewers of the credibility of your research means accepting the responsibility of preparing your research manuscript to commonly accepted standards in research.

As a result, seemingly insignificant things such as spelling mistakes, page numbers, and proper grammar can make a difference with a particularly strict reviewer. Even when you expect to develop a paper through reviewer comments and peer feedback, your manuscript should be as close to a polished final draft as you can make it prior to submission.

Qualitative researchers face particular challenges in convincing their target audience of the value and credibility of their subsequent analysis. Numbers and quantifiable concepts in quantitative studies are relatively easier to understand than their counterparts associated with qualitative methods . Think about how easy it is to make conclusions about the value of items at a store based on their prices, then imagine trying to compare those items based on their design, function, and effectiveness.

Qualitative research involves and requires these sorts of discussions. The goal of qualitative data analysis is to allow a qualitative researcher and their audience to make such determinations, but before the audience can accept these determinations, the process of conducting research that produces the qualitative analysis must first be seen as trustworthy. As a result, it is on the researcher to persuade their audience that their data collection process and subsequent analysis is rigorous.

Qualitative rigor refers to the meticulousness, consistency, and transparency of the research. It is the application of systematic, disciplined, and stringent methods to ensure the credibility, dependability, confirmability, and transferability of research findings. In qualitative inquiry, these attributes ensure the research accurately reflects the phenomenon it is intended to represent, that its findings can be understood or used by others, and that its processes and results are open to scrutiny and validation.

Transparency

It is easier to believe the information presented to you if there is a rigorous analysis process behind that information, and if that process is explicitly detailed. The same is true for qualitative research results, making transparency a key element in qualitative research methodologies. Transparency is a fundamental aspect of rigor in qualitative research. It involves the clear, detailed, and explicit documentation of all stages of the research process. This allows other researchers to understand, evaluate, replicate, and build upon the study. Transparency in qualitative research is essential for maintaining rigor, trustworthiness, and ethical integrity. By being transparent, researchers allow their work to be scrutinized, critiqued, and improved upon, contributing to the ongoing development and refinement of knowledge in their field.

Research papers are only as useful as their audience in the scientific community is wide. To reach that audience, a paper needs to pass the peer review process of an academic journal. However, the idea of having research published in peer-reviewed journals may seem daunting to newer researchers, so it's important to provide a guide on how an academic journal looks at your research paper as well as how to determine what is the right journal for your research.

In simple terms, a research article is good if it is accepted as credible and rigorous by the scientific community. A study that isn't seen as a valid contribution to scientific knowledge shouldn't be published; ultimately, it is up to peers within the field in which the study is being considered to determine the study's value. In established academic research, this determination is manifest in the peer review process. Journal editors at a peer-reviewed journal assign papers to reviewers who will determine the credibility of the research. A peer-reviewed article that completed this process and is published in a reputable journal can be seen as credible with novel research that can make a profound contribution to scientific knowledge.

The process of research publication

The process has been codified and standardized within the scholarly community to include three main stages. These stages include the initial submission stage where the editor reviews the relevance of the paper, the review stage where experts in your field offer feedback, and, if reviewers approve your paper, the copyediting stage where you work with the journal to prepare the paper for inclusion in their journal.

Publishing a research paper may seem like an opaque process where those involved with academic journals make arbitrary decisions about the worthiness of research manuscripts. In reality, reputable publications assign a rubric or a set of guidelines that reviewers need to keep in mind when they review a submission. These guidelines will most likely differ depending on the journal, but they fall into a number of typical categories that are applicable regardless of the research area or the type of methods employed in a research study, including the strength of the literature review , rigor in research methodology , and novelty of findings.

Choosing the right journal isn't simply a matter of which journal is the most famous or has the broadest reach. Many universities keep lists of prominent journals where graduate students and faculty members should publish a research paper , but oftentimes this list is determined by a journal's impact factor and their inclusion in major academic databases.

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This section is part of an entire guide. Use this table of contents to jump to any page in the guide.

Part 1: The Basics

• What is qualitative data?
• 10 examples of qualitative data
• Qualitative vs. quantitative research
• What is mixed methods research?
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research questions
• Conceptual framework
• Conceptual vs. theoretical framework
• Focus groups
• Observational research
• Case studies
• Survey research
• What is ethnographic research?
• Confidentiality and privacy in research
• Bias in research
• Power dynamics in research
• Reflexivity

Part 2: Handling Qualitative Data

• Research transcripts
• Field notes in research
• Research memos
• Survey data
• Images, audio, and video in qualitative research
• Coding qualitative data
• Coding frame
• Auto-coding and smart coding
• Organizing codes
• Content analysis
• Thematic analysis
• Thematic analysis vs. content analysis
• Narrative research
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Part 3: Presenting Qualitative Data

• Data visualization - What is it and why is it important?

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Present Your Data Like a Pro

• Joel Schwartzberg

Demystify the numbers. Your audience will thank you.

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

• JS Joel Schwartzberg oversees executive communications for a major national nonprofit, is a professional presentation coach, and is the author of Get to the Point! Sharpen Your Message and Make Your Words Matter and The Language of Leadership: How to Engage and Inspire Your Team . You can find him on LinkedIn and X. TheJoelTruth

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Top 5 Easy-to-Follow Data Presentation Examples

You’ll agree when we say that poring through numbers is tedious at best and mentally exhausting at worst.

And this is where data presentation examples come in.

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to relax or execute other tasks. Besides, when creating data stories, you need charts that communicate insights with clarity.

There are 5 solid and reliable data presentation methods: textual, statistical data presentation, measures of dispersion, tabular, and graphical data representation.

Besides, some of the tested and proven charts for data presentation include:

• Waterfall Chart
• Double Bar Graph
• Slope Chart
• Treemap Charts
• Radar Chart
• Sankey Chart

There are visualization tools that produce simple, insightful, and ready-made data presentation charts. Yes, you read that right. These tools create charts that complement data stories seamlessly.

Remember, without visualizing data to extract insights, the chances of creating a compelling narrative will go down.

Table of Content:

What is data presentation, top 5 data presentation examples:, how to generate sankey chart in excel for data presentation, importance of data presentation in business, benefits of data presentation, what are the top 5 methods of data presentation.

Data presentation is the process of using charts and graphs formats to display insights into data. The insights could be:

• Relationship
• Trend and patterns

Data Analysis  and  Data Presentation  have a practical implementation in every possible field. It can range from academic studies, and commercial, industrial , and marketing activities to professional practices .

In its raw form, data can be extremely complicated to decipher. Examples of data presentation, such as chord diagrams , are an important step toward breaking down data into understandable charts or graphs.

You can use tools (which we’ll talk about later) to analyze raw data.

Once the required information is obtained from the data, the next logical step is to present it in a graphical presentation, such as a Box and Whisker presentation .

The presentation is the key to success.

Once you’ve extracted actionable insights, you can craft a compelling data story. Keep reading because we’ll address the following in the coming section: the importance of data presentation in business, including how tools like a Sunburst Chart can enhance your analysis.

Let’s take a look at the five data presentation examples below:

1. Waterfall Chart

A Waterfall Chart is a graphical representation used to depict the cumulative impact of sequential positive or negative values on a starting point over a designated time frame. It typically consists of a series of horizontal bars, with each bar representing a stage or category in a process.

2. Double Bar Graph

A Double Bar Chart displays more than one data series in clustered horizontal columns, similar to a clustered stacked bar chart . Each data series shares the same axis labels, so horizontal bars are grouped by category.

This arrangement allows for direct comparison of multiple series within a given category. The chart is amazingly easy to read and interpret, even for a non-technical audience.

3. Slope Chart

Slope Charts are simple graphs that quickly and directly show  transitions, changes over time, absolute values, and even rankings .

Besides, they’re also called Slope Graphs .

This is one of the data presentation examples you can use to show the before and after story of variables in your data.

Slope Graphs can be useful when you have two time periods or points of comparison and want to show relative increases and decreases quickly across various categories between two data points.

A TreeMap is a data structure that stores key-value pairs in a sorted order using a Red-Black tree, ensuring efficient search, insertion, and deletion operations.

Take a look at the table below. Can you provide coherent and actionable insights into the table below?

Notice the difference after visualizing the table. You can easily tell the performance of individual segments in:

• Macy’s Store

5. Radar Chart

Radar Chart is also known as Spider Chart or Spider Web Chart. A radar chart is very helpful to visualize the comparison between multiple categories and variables.

A radar Chart is one of the data presentation examples you can use to compare data of two different time ranges e.g. Current vs Previous. Radar Chart with different scales makes it easy for you to identify trends, patterns, and outliers in your data. You can also use Radar Chart to visualize the data of Polar graph equations.

6. Sankey Chart

You can use the Sankey Chart to visualize data with flow-like attributes, such as material, energy, cost, etc.

This chart draws the reader’s attention to the enormous flows, the largest consumer, the major losses , and other insights.

The aforementioned visualization design, including the Mosaic plot presentation , is one of the data presentation examples that use links and nodes to uncover hidden insights into relationships between critical metrics.

The size of a node is directly proportionate to the quantity of the data point under review.

So how can you access the data presentation examples (highlighted above)?

Excel is one of the most used tools for visualizing data because it’s easy to use. 

However, you cannot access ready-made and visually appealing data presentation charts, such as a funnel chart , for storytelling. But this does not mean you should ditch this freemium data visualization tool .

Did you know you can supercharge your Excel with add-ins to access visually stunning and ready-to-go data presentation charts?

Yes, you can increase the functionality of your Excel and access ready-made data presentation examples for your data stories.

The add-on we recommend you to use is ChartExpo.

What is ChartExpo?

We recommend this tool (ChartExpo) because it’s super easy to use.

You don’t need to take programming night classes to extract insights from your data. ChartExpo is more of a ‘drag-and-drop tool,’ which means you’ll only need to scroll your mouse and fill in respective metrics and dimensions in your data, whether you’re working with Mekko presentation or other visualizations.

ChartExpo comes with a 7-day free trial period.

The tool produces charts that are incredibly easy to read and interpret . And it allows you to save charts in the world’s most recognized formats, namely PNG and JPG.

In the coming section, we’ll show you how to use ChartExpo to visualize your data with one of the data presentation examples (Sankey).

  To install ChartExpo add-in into your Excel, click this link .

• Open your Excel and paste the table above.
• Click the My Apps button.

• Then select ChartExpo and click on  INSERT, as shown below.

• Click the Search Box and type “Sankey Chart” .

• Once the chart pops up, click on its icon to get started.

• Select the sheet holding your data and click the Create Chart from Selection button.

How to Edit the Sankey Chart?

• Click the Edit Chart button, as shown above.

• Once the Chart Header Properties window shows, click the Line 1 box and fill in your title.

• To change the color of the nodes, click the pen-like icons on the nodes.
• Once the color window shows, select the Node Color and then the Apply button.

• Save your changes by clicking the Apply button.
• Check out the final chart below.

Data presentation examples are vital, especially when crafting data stories for the top management. Top management can use data presentation charts, such as Sankey, as a backdrop for their decision.

Presentation charts, maps, and graphs are powerful because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Big files with numbers are usually hard to read and make it difficult to spot patterns easily. However, many businesses believe that developing visual reports focused on creating stories around data is unnecessary; they think that the data alone should be sufficient for decision-making.

Visualizing supports this and lightens the decision-making process.

Luckily, there are innovative applications you can use to visualize all the data your company has into dashboards, graphs, and reports. Data visualization helps transform your numbers into an engaging story with details and patterns.

Check out more benefits of data presentation examples below:

1. Easy to understand

You can interpret vast quantities of data clearly and cohesively to draw insights, thanks to graphic representations.

Using data presentation examples, such as charts, managers and decision-makers can easily create and rapidly consume key metrics.

If any of the aforementioned metrics have anomalies — ie. sales are significantly down in one region — decision-makers will easily dig into the data to diagnose the problem.

2. Spot patterns

Data visualization can help you to do trend analysis and respond rapidly on the grounds of what you see.

Such patterns make more sense when graphically represented; because charts make it easier to identify correlated parameters.

3. Data Narratives

You can use data presentation charts, such as Sankey or Area Charts , to build dashboards and turn them into stories.

Data storytelling can help you connect with potential readers and audiences on an emotional level.

4. Speed up the decision-making process

We naturally process visual images 60,000 times faster than text. A graph, chart, or other visual representation of data is more comfortable for our brain to process.

Thanks to our ability to easily interpret visual content, data presentation examples can dramatically improve the speed of decision-making processes.

Take a look at the table below.

Can you give reliable insights into the table above?

Keep reading because we’ll explore easy-to-follow data presentation examples in the coming section. Also, we’ll address the following question: what are the top 5 methods of data presentation?

1. Textual Ways of Presenting Data

Out of the five data presentation examples, this is the simplest one.

Just write your findings coherently and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture.  Yes, you read that right.

The introduction, summary, and conclusion can help condense the information.

2. Statistical data presentation

Data on its own is less valuable. However, for it to be valuable to your business, it has to be:

No matter how well manipulated, the insights into raw data should be presented in an easy-to-follow sequence to keep the audience waiting for more.

Text is the principal method for explaining findings, outlining trends, and providing contextual information. A table is best suited for representing individual information and represents both quantitative and qualitative information.

On the other hand, a graph is a very effective visual tool because:

• It displays data at a glance
• Facilitates comparison
• Reveals trends, relationships, frequency distribution, and correlation

Text, tables, and graphs are incredibly effective data presentation examples you can leverage to curate persuasive data narratives.

3. Measure of Dispersion

Statistical dispersion is how a key metric is likely to deviate from the average value. In other words, dispersion can help you to understand the distribution of key data points.

There are two types of measures of dispersion, namely:

• Absolute Measure of Dispersion
• Relative Measure of Dispersion

4. Tabular Ways of Data Presentation and Analysis

To avoid the complexities associated with qualitative data, use tables and charts to display insights.

This is one of the data presentation examples where values are displayed in rows and columns. All rows and columns have an attribute (name, year, gender, and age).

5. Graphical Data Representation

Graphical representation uses charts and graphs to visually display, analyze, clarify, and interpret numerical data, functions, and other qualitative structures.

Data is ingested into charts and graphs, such as Sankey, and then represented by a variety of symbols, such as lines and bars.

Data presentation examples, such as Bar Charts , can help you illustrate trends, relationships, comparisons, and outliers between data points.

What is the main objective of data presentation?

Discovery and communication are the two key objectives of data presentation.

In the discovery phase, we recommend you try various charts and graphs to understand the insights into the raw data. The communication phase is focused on presenting the insights in a summarized form.

What is the importance of graphs and charts in business?

Big files with numbers are usually hard to read and make it difficult to spot patterns easily.

Presentation charts, maps, and graphs are vital because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Poring through numbers is tedious at best and mentally exhausting at worst.

This is where data presentation examples come into play.

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to handle other tasks. Besides, when creating data stories, it would be best if you had charts that communicate insights with clarity.

Excel, one of the popular tools for visualizing data, comes with very basic data presentation charts, which require a lot of editing.

We recommend you try ChartExpo because it’s one of the most trusted add-ins. Besides, it has a super-friendly user interface for everyone, irrespective of their computer skills.

Create simple, ready-made, and easy-to-interpret Bar Charts today without breaking a sweat.

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